Citation
Acoustically measured postural stability with visual feedback

Material Information

Title:
Acoustically measured postural stability with visual feedback
Creator:
Shuman, Dennis, 1946- ( Dissertant )
Doty, Keith L. ( Thesis advisor )
White, Keith D. ( Reviewer )
Berg, W. Keith ( Reviewer )
Childers, Donald G. ( Reviewer )
Dawson, William W. ( Reviewer )
Place of Publication:
Gainesville, Fla.
Publisher:
University of Florida
Publication Date:
Copyright Date:
1987
Language:
English
Physical Description:
xii, 226 leaves : ill. ; 28 cm.

Subjects

Subjects / Keywords:
Buffer storage ( jstor )
Bytes ( jstor )
Error rates ( jstor )
Microcomputers ( jstor )
Negative feedback ( jstor )
Retinal images ( jstor )
Signals ( jstor )
Software ( jstor )
Timing devices ( jstor )
Vibration ( jstor )
Dissertations, Academic -- Electrical Engineering -- UF
Electrical Engineering thesis Ph. D
Equilibrium (Physiology) ( lcsh )
Equilibrium (Physiology) -- Data processing ( lcsh )
City of Gainesville ( local )
Genre:
bibliography ( marcgt )
non-fiction ( marcgt )

Notes

Abstract:
Postural stability is a function of several weighted sensory inputs to a central neural controller. A new laboratory tool was developed to help quantify body sway performances in general and to explore the contribution of visual input as a feedback control signal in particular. By utilizing body sway data collected online for the control of a surrounding pattern’s movement, the visual feedback loop was altered to permit further characterization of postural control. A parallel processing microcomputer system measured body sway in any direction, and generated visual stimuli based on mathematical analyses of the incoming sway data. Position and orientation determinations were accomplished by ascertaining the transit times of sequential sound fronts from head attached acoustic sources to an array of fixed receivers surrounding the subject. With two sources employed, sampling rates of 25 Hz were achieved with position and orientation accuracies better than 1 mm and 0.2” within a volume sufficiently large to accommodate the extreme limits of body sway. The system managed the horizontal position of a vertical grid shadow cast upon a vertically oriented cylindrical screen encompassing the subject’s field of view. When governed by the sway data, the grid position response delay introduced was less than 90 msec, and the position accuracy was better than 0.5” over its full 32” range with unity feedback gain. A study of 33 subjects employing stimulus movements governed by body sway, with feedback gains ranging from -2 to +2, demonstrated differential influences on sway frequency spectra by absolute and relative (to those normally expected) retinal image motions. Only stimulus movements that were both spatially and temporally correlated with sway behaved as true feedback control. Sway spectra thus observed were ordered directly with positive feedback gains and inversely with negative feedback gains. Additionally, those spectra exhibited large peaks and valleys that displayed frequency consistency across feedback gain magnitudes but reversed with feedback gain polarity. The importance of regarding sway energy about 1 Hz was confirmed.
Thesis:
Thesis (Ph. D.)--University of Florida, 1987.
Bibliography:
Bibliography: leaves 221-224.
General Note:
Typescript.
General Note:
Vita.
Statement of Responsibility:
by Dennis Shuman.

Record Information

Source Institution:
University of Florida
Holding Location:
University of Florida
Rights Management:
Copyright Dennis Shuman. Permission granted to the University of Florida to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Resource Identifier:
030338623 ( ALEPH )
16818207 ( OCLC )
AEQ4836 ( NOTIS )

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Full Text












ACOUSTICALLY MEASURED POSTURAL STABILITY
WITH VISUAL FEEDBACK




By

DENNIS SHUMAN


A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN
PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY


UNIVERSITY OF FLORIDA


1987

..





































Copyright 1987

by

Dennis Shuman

..













ACKNOWLEDGMENTS


I feel honored and extremely grateful to have worked with and learned from Dr. Keith White, my cobchair and research advisor. Dr. White's brilliance was a continual source of awe and inspiration _to, me, and -Omhi+nd with his pr-a -ical ro-rDnrcefulnpss, taught me muh abOu t cDnducting research. However, the education I received.from him far exceeded academia, for Dr. White is one of the most caring, loving, and self-sacrificing human beings Tshave encountered in my life. His dedication to his students;ehis colleagues, and his wife, as well as the countless timesehe has compassionately bent over backwards to hdlpeand support me, I will never forget. etI would also like to express my appreciation to my

c-hair, Jr. eeith Doty, for his encouragemenz-In the pursuit of my degree, and to my committee members, Dt. Keith Berg, Dr. Don Childers, and Dr. Bill Dawson, for their guidance and support during my many years of association with them. Additionally, I want to thank Dr. Shelly Isemberg for helping me maintain a semblance of perspective and sanity through it all.

I am deeply indebted to the administrative staffs in

-both the Departments -of Electrical Engineerig and


iii

..







Psychology, with special thanks to Jim Fitzgerald, Cheryl Phillips, Dotty Starry, and Doris Thames. I want to acknowledge the help provided by all my fellow.research assistants, especially John Krantz, Pascal programmer and "fellow swayer". To my subjects, all those friends who voluntarily submitted themselves to my torture machine in order that I might leave the ranks of student serfdom, gracias!

Finally, I want to give thanks to mychildren Yossi and baby Meira for giving me the inspiration and need-to finish being a student, to my wife Renee for putting up with-ny perfectionism, and to my parents who instilled ihis questionable trait in me so that one day they might kvell

"my son, the doctor".

..
















TABLE OF CONTENTS



ACKNOWLEDGMENTS.iii

LIST OF FIGURES.viii

KEY TO SYMBOLS AND ABBREVIATIONS.x

ABSTRACT.xi

CHAPTERS

1INTRODUCTION.1

1.1 Postural Overview.1 1.2 Previous Postural Stability Studies . 4
1.3 Methods Used in Postural Studies. .16
1.3.1 Measurement Issues.16 1.3.2 Previous Postural Measuring Systems 18 1.3.3 Previous Stimulus Feedback Systems 23 1.3.4 Position Sensor System Overview . 25
1.4 Proposed Study.27

2 POSITION SENSOR SYSTEM DESIGN AND DEVELOPMENT . 33

2.1 Data Acquisition Subsystem .33
2.1.1 DAS Hardware.35 2.1.2 DAS Geometric Analysis.49 2.1.3 DAS Software.55 2.1.4 DAS Characterization.63
2.2 Stimulus Control Subsystem .68
2.2.1 SCS Hardware.68 2.2.2 SCS Geometric Analysis.69 2.2.3 SCS Software.73 2.2.4 SCS Characterization.89
2.3 Stimulus Projection Subsystem.90
2.3.1 SPS Construction.91 2.3.2 SPS Calibration and Performance . . 96
2.4 Feedback Stimulus Characterization. .98

..







3 EXPERIMENTAL METHOD. 10


3.1 Subjects.104 3.2 Procedure.105
3.2.1 Experimental Environment.105 3.2.2 Subject Information and Instructions -110 3.2.3 Trial Parameters.111
3.3 Data Analysis.115
4 EXPERIMENTAL RESULTS.118

5 DISCUSSION.136

5.1 Position Sensor System.136
5.1.1 Performance.136 5.1.2 Applications.140
5.2 Experiment.141
5.2.1 Informal Observations.141
5.2.2 Spatial Correlation and
Postural Performances .142 5.2.3 Altered Visual Feedback .146
5.2.4 Absolute and Relative
."Retinal Image Motion". .152
5.2.5 Summary.159

APPENDICES

A DAS SOFTWARE.161

A.1 CTRL.BAS Code.161 A.2 CTRL.BAS Explanatory Notes.163 A.3 DAS Memory Map.165 A.4 CTRL.MLP Code.166

B CALIBRATED MECHANICAL TRANSPORT SYSTEM .170

C D/A CONVERTER IMPLEMENTATION.173

C.1 Circuit Description.173 C.2 Calibration.178


104

..








D SCS SOFTWARE . . . . . . . .


D.1 Operating System Interrupt Correction D.2 DSTIM.BAS Code . . . . . .
D.3 DSTIM.BAS Explanatory Notes . . D.4 SCS Memory Map . . . . . .
D.5 SCS Machine Language Routines . .
D.5.1 DYNHAND Code . .
D.5.2 ERROR.MLP Code . . . .
D.5.3 TERM.MLP Code . . . . .
D.5.4 VAR.MLP Code . . . . .
D.5.5 EQRUN.MLP Code . . . . .
D.5.6 D/A.MLP Code . . . . .
D.6 Stimulus Jitter Simulation . . .


S. 180 . . 182 . . 186
. . 191 S. . 195 S . 195
196 S . 200 S. . 201
202 . . 204 . . 206


REFERENCES . . . . . . . . . .

BIOGRAPHICAL SKETCH . . . . . . . .


213

217


vii


. . 180

..


















Figure

1.


LIST OF FIGURES



Position Sensor System Component Sections .


2. Acoustic Source Driver and
Synchronization Circuit Components with Operational Waveforms.

3. Microphone/Detector Circuitry
with Operational Waveforms.

4. PSS Geometry: Head Localization
and Stimulus Angle Determination.

5. DAS Software Flowchart:
Online Operation .

6. SCS Software Flowchart:
Online Operation for
Stimulus Feedback Trials .

7. Lateral Sway Gains with
Positive Stimulus Feedback Gains.

8. Lateral Sway Gains with
Negative Stimulus Feedback Gains.

9. Lateral Sway Gains Referenced to
Stationary Stimulus Condition.

0. Anteroposterior Sway Gains with
Positive Stimulus Feedback Gains.

1. Anteroposterior Sway Gains with
Negative Stimulus Feedback Gains.

2. Anteroposterior Sway Gains Referenced
to Stationary Stimulus Condition.

3. Rotational Movement Gains with
Positive Stimulus Feedback Gains.


viii


Pa3e

36


40


. . 45 . 52 . 59 . 79 . 120 S . 121 . 122 . 123 . 124 . 125 . 126


1


1


1


1

..







14. Rotational Movement Gains with
Negative Stimulus Feedback Gains .127

15. Rotational Movement Gains Referenced
to Stationary Stimulus Condition .128

16. D/A Converter Circuit Implementation
with Operational Waveforms. .176

17. DAS Rotational Angle Data Distribution
with Stationary Headpiece for
Generation of Jitter Simulation. .2-09

..















KEY TO SYMBOLS AND ABBREVIATIONS


Abbr

CMTS Calibrated Mechanical Transport System used in the
characterization of the PSS.

Cl The stimulus microcomputer, a component of the SCS.

C2 The position microcomputer, a component of the DAS. D/A Digital to Analog conversion. DAS Data Acquisition Subsystem of the PSS.

$ A prefix indicating a hexidecimal number. DPS Data Processing Subsystem of the PSS. DSB Data Storage Block, a dedicated- area of memory in C2. mic Microphone or microphone/detector. PSS Position Sensor System. rad A unit of length defined as the radius of rotation of the cylindrical screen (component of the SPS). SCS Stimulus Control Subsystem of the PSS. sp Speaker, click source, or acoustic source. SPS Stimulus Projection Subsystem of the PSS. e Stimulus angle or stimulus projection angle.

VIA Versatile Interface Adapter, an I/O control device
(Synertek SY6522A).

..















Abstract of Dissertation Presented to the Graduate School. of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy


ACOUSTICALLY MEASURED POSTURAL STABILITY WITH VISUAL FEEDBACK

By

DENNIS SHUMAN

May, 1987

Chairman: Dr Keith L. Doty Cochairman: Dr Keith D. White Major Department: Electrical Engineering

Postural stability is a function of several weighted sensory inputs to a central neural controller. A new laboratory tool was developed to help quantify body sway performances in general and to explore the contribution of visual input as a feedback control signal in particular. By utilizing body sway data collected online for the c-ontrol of a surrounding pattern's movement, the visual feedback loop was altered to permit further characterization of postural control.

A parallel processing microcomputer system measured body sway in any direction, and generated visual stimuli based on mathematical analyses of the incoming sway data. Position and orientation determinations were accomplished by ascertaining the transit times of sequential sound fronts

..







from head attached acoustic sources to an array of fixed receivers surrounding the subject. With two sources employed, sampling rates of 25 Hz were achieved with position and orientation accuracies better than 1 mm and

0.20 within a volume sufficiently large to accommodate the extreme limits of body sway. The system managed the horizontal position of a vertical grid shadowcast upon a vertically oriented cylindrical screen encompassing the subject's field of view. When governed by the sway data, the grid position response delay introduced was less than 90 msec, and the position accuracy was better than 0.50 over its full 320 range with unity feedback gain.

A study of 33 subjects employing stimulus movements

governed by body sway, with feedback gains ranging from -2 to +2, demonstrated differential influences on sway frequency spectra by absolute and relative (to those normally expected) retinal image motions. Only stimulus movements that were both spatially and temporally correlated with sway behaved as true feedback control. Sway spectra thus observed were ordered directly with positive feedback gains and inversely with negative feedback gains. Additionally, those spectra exhibited large peaks and valleys that displayed frequency consistency across feedback gain magnitudes but reversed with feedback gain polarity. The importance of regarding sway energy above 1 Hz was confirmed.


xii

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CHAPTER 1
INTRODUCTION





1.1 Postural Overview



People are inherently unstable. While this statement might prove to be quite controversial to a developmental psychologist, it would not even begin to raise the eyebrows of a sensory psychologist. The problem is familiar to anyone who has watched a child learning how to stand. The most commonly used model of an upright person is an inverted pendulum. In static mechanistic terms, a body will fall if its center of gravity is positioned outside its base of support. Even a person with a size 11 shoe still has a lot to contend with. Fortunately, we are endowed with muscles which can exert forces on our skeletal frames to keep us upright in a kind of dynamic quasi-stability. However, these muscles need to be kept informed as to which way they should pull, with how much force, and when. The requisite information helps provide us with what is referred to as spatial orientation, the sense of where one's body is and how it is moving in relation toits environment. This is

..







2

supplied by our sensory inputs which function as our interface with our surroundings.

Although any sensory inputs can provide positional

cues, it is well recognized that the visual, vestibular, and proprioceptive senses play the dominant roles under most circumstances. These sensory inputs are processed by the nervous system which, in conjunction with assumptions based on past experience, provides our spatial orientation and decides what course of action to pursue. In situations where all the inputs are interpreted as being in concordance, the nervous system generally performs its function superbly. The various inputs are not necessarily redundant, but are rather in harmony, in that they provide different facets of the overall situation. In addition, their different resolution and frequency response (bandwidth) properties make their relative value vary in assorted situations, and the nervous system uses its own program to weight these sensory inputs accordingly.- The problem arises when the received information is insufficient, misleading, novel, or conflicting. It is then that disorientation, and possibly even physical disturbances, can occur. The degree of disorientation is a function of the weighting enacted by the nervous system, and this program is apparently very individualistic and adaptable. It is difficult to get a good objective measure of disorientation, but one method that has been commonly used is to measure postural stability or body sway. This

..







3

leads to another problem which is how to quantitatively define and measure this parameter? This is one of the issues addressed by this paper.

With the ability to measure spatial orientation, it becomes possible to evaluate the role of, and gain an operational understanding of, any one sensory input. In many situations, visual perception plays the dominant role, and sometimes with counterproductive results. Most people have experienced the power of vision in establishing spatial orientation while sitting in a stationary vehicle and watching the vehicle next to them as it begins to move. Often, the overwhelming sensation is that they are the ones that are moving. There are many places where it is possible to view movies projected on 360* screens, and it is not uncommon for people to lose their balance and/or experience motion sickness while watching these panoramas filmed from moving vehicles. In both of these situations the visual cues dominate the other conflicting sensory inputs,-compelling a false sense of self motion. In contrast, travel sickness experienced inside a moving vehicle results from the dominating, misleading visual cue of a still surround in conflict with vestibular cues conveying the true situation. This predicament is of special interest in space flight where gravity, and its relationship to the surrounding environment, can no longer be treated as constants.

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4

Vision performs a direct feedback role when conveying information about body sway. A person overlooking a vista will exhibit an decrease in postural stability, and thus a greater tendency of falling, due to the decrease in retinal image motion that occurs during sway while viewing a distant object. Similarly, a new prescription for corrective lenses can degrade stability due to the altered relationship between head movement and retinal image motion. A greater understanding of the role of visual feedback in balance, studied by non-invasive means, holds the potential of revealing significant contributory factors which induce disorientation and thus promote falling. It is hoped that this study will suggest possible remedies to reduce the influence of these factors.





1.2 Previous Postural Stability Studies



The fact that visual information plays an important

role in the regulation of posture has been well appreciated. A person standing with eyes open will exhibit spontaneous postural sway which will increase in amplitude by up to 50% when the eyes are closed. An example of this kind of test is the classic Romberg test, which has been used as a diagnostic aid based on the fact that postural stability also largely depends upon vestibular and proprioceptive information. Patients with diseases involving these other

..







5

systems show markedly increased closed eye body sway as compared to normal subjects. However, the general applicability of the Romberg test has come under question.

The dynamics of the influences on postural stability is exceedingly complex, as can be appreciated by reviewing the disconnected and sometimes contradictory data published to date. Some of this divergent data is apparently the result of the subtleties of these influences in particular experimental designs, as well as the lack of uniformity in what parameters are measured and the methods for doing so. As examples, Brocklehurst et al. (1982) reported not finding a correlation between visual deprivation and postural sway, and Litvinenkova and Hlavacka (1971, cited by Gantchev et al., 1972) found that in dark adaptation, closing the eyes actually reduced body oscillations. Another seemingly surprising contradiction was uncovered by Nashner and Berthoz (1978). In examining the transient responses of subjects to an unexpected movement of a platform upon which they were standing (which were termed "early motor responses"), they found that no difference in postural performance (as measured by the body pitch and the EMG activity of gastrocnemius or ankle extensor muscles) between normal eyes opened and eyes closed conditions. Only in the condition of a visual field stabilized with respect to the subject's head was there a degradation in postural performance. Thus false visual information did affect response, but the lack of visual information did not degrade

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6

it. Apparently, the weighting of the visual information was somehow being altered.

The interaction between these three (visual,

proprioceptive and vestibular) systems in the control of postural stability is quite complex and not well understood. It should be noted that other systems can provide stabilizing cues which can be significant, especially during the lack of information from these three major sensory systems. Examples are somesthetic (e.g., via a blind person's cane) and auditory cues. Some experimenters have had their subjects wear headphones transducing white noise to eliminate extraneous auditory cues. The relative weighting by the body of these sensory systems is very individualistic and situationally dependent. Lestienne et al. (1977), using a moving visual scene to induce postural instability, found little or no effect with 20% of the subjects. Most of these subjects then exhibited the more typical instability when asked to perform mental arithmetic while the stimulus was present, demonstrating not only individual differences but also the subtlety of the weighting factors. This is probably related to what Witkin (1959) refers to as the two personality types. Field dependent subjects sense their orientation with respect to their (visual) surroundings, have lower IQs and are more dependent on others. Field independent subjects sense their orientation with respect to their internal "feel" in relationship to gravity (vestibular), and individuals tend

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7

to become more field independent as they age. This might help explain the strong correlation between age and increased postural sway (Era and Heikkinen, 1985). As seen above, the typical sensory weighting pattern of the field independent subject can sometimes be altered by a mental distraction. Dorman et al. (1978) discusses how a distraction as well an anxiety, inattention or diminished eye fixation, can degrade postural stability, and is probably related to the alteration of sensory weightings. Vidal et al. (1982) notes that even the instructions given to subjects can alter sensory weightings and postural performance. If a subject is told that he can grab a fixed metal bar to restore his equilibrium if necessary there can be even complete suppression of the normal stabilizing motor reflex in the lower limbs, even though the cues transmitted from peripheral sensory systems are unaltered.

In general, the studies performed on postural stability involved the stimulation of one or more of the sensory systems while either leaving the others intact or altering them (usually to diminish -their effect). When the resulting spatial information signalled by the various sensory channels is in conflict rather than accord, sometimes a single sensory channel determines the apparent spatial orientation of the body. Gonshor and Jones (1980) investigated vision reversal produced by wearing dove prisms to produce horizontal inversion and reversed relative lateral movement of the visual image. In spite of

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8

appropriate vestibular and proprioceptive feedback, there was a strong hierarchical predominance of vision resulting in a violent loss of balance. In contrast to this, Nashner (1982) found that unexpected functionally inappropriate visual orientation cues do not always play a major role in determining anteroposterior postural performance. He proposed that the rapid reweighting of sensory inputs is established by a fixed higher level process. He postulated that the short term weighting of proprioceptive and visual inputs is a function of the congruence of each of these senses with the inertial-gravitational reference provided by the vestibular system and that conflicting inputs from these two senses are quickly suppressed in favor of those congruent with the vestibular reference. Patients with vestibular deficits (Nashner et al., 1982) and children below the age of 7 1/2 years (Forssberg and Nashner, 1982) do not have this higher level vestibular function to reweight sensory inputs when they are conflicting, and so experience greater instability than when just deprived of these sensory inputs.

The idea of some pre-established strategy for rapid

resolution of conflict based on an internal reference system is also found in the concept of "efference copy." According to this theory, knowledge of intended movements is used to construct an "internal model" of orientation which is used to distinguish between shifts in body orientation relative to the surround and changes in orientation of external

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objects relative to the body. Nashner et al. (1982) were concerned that a limitation of this concept in explaining the observed phenomena is when reorientation of the body occurs without prior knowledge, as when due to the inherently unstable characteristics of the body in the presence of external perturbations. Incorporation of a memory-like process and less reliance upon the intentional nature of movements mitigates those concerns to some extent (Held, 1961).

A moving visual scene can induce a sensation of

self-motion called vection. Dichgans and Brandt (1978) state that it is very likely that the afferent physiologic mechanisms involved with vection are identical with those stabilizing posture. When a subject views a moving visual environment, a conflict is induced between the changing visual input, which can be interpreted as body movement, and vestibular and proprioceptive information which detect no movement. Often, this conflict leads to disorientation and motion sickness as well as increased postural sway. Lestienne et al. (1977) attributed increased postural oscillations during a constant velocity moving visual scene to the visual-vestibular conflict reducing their "weight ratio" in favor of proprioceptive input. This enhancement or increased gain of the proprioceptive feedback loop would cause overcompensation and thus oscillation. Another example of the interactions between systems during conflict was shown by Lackner and Teixeira (1977). They found that

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10

although visual stimulation usually dominates vestibular input, if a strong (continuously changing) vestibular and proprioceptive input is generated by continuous and periodic head movement, the effect of the visual stimulation was lessened. This they likened to the domination of other senses over vision when the retinal image is stable. They concluded that covarying patterns of sensory change from a number of receptor systems allow a more accurate assessment of ongoing orientation because of less opportunity for adaptation when the input is changing and because a changing sensory input is "weighted" more heavily in determining ongoing orientation. For convenience, this is termed the "stimulus magnitude effect."
I
Teixeira and Lackner (1979) also found that as the

velocity of the visual stimulation was increased the greater frequency of voluntary head movements needed to prevent visual dominance of apparent orientation. However, the issue could be raised that moving the head also increases retinal image motion. The situation is complicated by the fact that sometimes retinal image motion is accompanied by a lowered weighting of vision as was found by White et al. (1980) during saccadic eye movements. This is necessary to prevent loss of balance during eye movement that is initiated by the nervous system. However, White et al. (1980) also found that retinal image motion caused by external perturbation of the eyeball is not accompanied by a lowered visual weighting, and postural stability is

..









disrupted. This implies that it is not eyeball movement itself that is affecting weighting but perhaps eyeball motor commands. Self initiated head movements also result in retinal image motions that need to be suppressed for maintenance of balance. Interestingly, Teixeira and Lackner (1979) disproved the possibility that inhibition of the visual stimulation effects was due to suppression by head motor commands during voluntary movement by replicating their previous results with passive (mechanically controlled) head movements. Also the fact that either rotary or tilting head movements produced similar results is noted. In the Gonshor and Jones (1980) study with optical reversal of vision, they found that there was progressive recovery of postural control after donning the prisms in walking tests but not in the standing tests. Although they did not understand why, perhaps this was due to increased proprioceptive and vestibular input (during walking) having the effect of reducing the weighting of visual input. Another example of this "stimulus magnitude effect" on relative weighting is shown by Lestienne et al. (1977) In their study of the influence of linear motion of a visual scene on postural sway, they found that the sway amplitude was proportional to area of the retina stimulated.

Another factor that influences the relative weighting of the various stimuli is the current state of postural stability. By comparing postural performances of subjects on a stationary platform and one perturbed to induce body

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sway, Soechting and Berthoz (1979) concluded that visual stimulus motion produces a greater effect when tested in a dynamic condition of postural change than when tested in isolation in a static posture maintenance condition. This might be likened to the difference between transient and steady state performance, both necessary for full characterization of a system.

The effect of altering the relationship between a

subject's movement and the resulting retinal image motion (visual feedback) has already been alluded to. The condition of a stabilized visual field, used in many studies (e.g., Nashner and Berthoz, 1978 and Vidal et al., 1982), involved a visual surround which tracked the anteroposterior motion of a subject's head, thus attempting to eliminate the subject's visual sense of motion. The stabilized visual stimulus was always initially more effective in degrading postural stability than an eyes closed condition. Vidal et al. (1982) concluded that the eyes closed condition-could not be considered visual deprivation but rather a tactic that reduces visual weighting, and that the stabilized condition results in an important disorganization of postural control. Nashner and Berthoz (1978) also tried moving the visual surround in the opposite direction of the subject's head to enhance the visual input (any anteroposterior movement of the subject appeared greater than it really was), with a resulting reduction in body sway. In a study (not true visual feedback) by Soechting

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and Berthoz (1979), the subject was accelerated in a cart while viewing a stimulus simulating one of three conditions corresponding to viewing just the motion of the cart, the stationary ground, or twice the cart motion. The angular displacement of body was similar in the first two conditions but was much greater in the latter condition. Their interpretation was that the first two conditions simulated normally encountered experiences but that the latter condition did not. In the Gonshor and Jones (1980) study with dove prisms, retinal image motion resulting from lateral body sway had the same magnitude but was in the opposite direction from normal. This extremely abnormal situation gave a subject the impression of moving in a direction opposite of the body's actual movement, resulting in severe instability. The relationship between retinal image motion and head motion can be thought of as a retinal image feedback gain. Gantchev and Koitcheva (1981) artificially simulated this feedback by having a subject's anteroposterior sway controlling the vertical movement of a horizontal line on a monitor viewed by the subject. They found that increasing the gain (the movement of the horizontal line) resulted in a decrease in body sway. In another study using the same system, Gantchev et al. (1981) found that reversing the direction of motion of the horizontal line did not significantly effect body sway but

-that introducing a delay in the visual feedback did. The degradation in postural stability was greater with a

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320 msec delay than with a 1200 msec delay (although the delayed feedback performance was still an improvement over the no feedback condition). Their conclusion was that the degradation was a function of the phase relationship between the delay and oscillatory characteristics of the body sway.

In the study of postural stability, another factor that needs to be accounted for is plasticity and adaptation. Leibowitz and Post (1980) describe their theory of the "two-visual systems" concept with a focal mode for object recognition and identification, and an "ambient" mode which mediates spatial orientation, locomotion and posture. The ambient mode is highly plastic and adaptable. For example, Nashner and Berthoz (1978) found rapid habituation of the influence of discongruent visual stimuli on EMG activity of leg muscles (used in assessing stabilization performance of the body) during repeated exposures. Their study also showed how the motor system reweights the visual, vestibular and proprioceptive inputs to postural control following changes in the conditions of stimulation. They concluded that visual inputs exert functionally different influences upon two postural control responses, early and late. The early response is immediately attenuated (as seen in EMG activity) upon reception of any unexpected discongruent visual input until the conflict is resolved. The late response is compensatory, optimizing postural control with the given sensory inputs. A more recent paper (Nashner et al., 1982) states that the rapid reweighting of sensory

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inputs utilizing a fixed internal model of the sensory context, is not adaptive in the true sense of the term. Adaptive changes in strategy which accompany modification of the internal model occur over a much longer time interval when the model fails to distinguish among self and external object motions within a new sensory context. Such adaptation was observed by Gonshor and Jones (1980) when subjects donned and later removed reversing prisms. An unexpected result they found was a marked and rapid deterioration of non-visual performance after the subjects began wearing the prisms, indicating that during adaptation the non-visual postural stabilizing systems were undergoing modification.

In summary, this review of what is known about the role of visual cues in the stabilization of posture presents a lot of fragmented bits and pieces that have yet to be put together to show the whole picture. Some of these pieces do not seem to fit, perhaps owing to the variety of experimental methods, the sensitivity and individuality of subjects' sensory weighting processes, and different interpretations of data. It is hoped that the new apparatus introduced here, and the research made possible by its development, will help in the clarification of these issues.

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1.3 Methods Used in Postural Studies



As technology has advanced, it has continually opened new doors of inquiry into the operation of nature's most sophisticated systems. In this modern age of computers, it is now feasible to build instruments that can interact online with biological systems, as well as collect and analyze hugh amounts of data about them. Such technological innovations presumably can extract new understanding of how nature normally performs its functions, and well as provide new means of assessing defective behavior.





1.3.1 Measurement Issues



There is not general agreement in the literature as to what is the most appropriate gauge of postural stability. If the body is assumed to behave as a rigid inverted pendulum, then measuring the movement of any part will define the movement of the whole. In actuality, the human musculoskeletal system constitutes an active articulated mechanism of extraordinary complexity with its 240 or so degrees of freedom powered by approximately 750 individual muscles. The correlation between the movement of any two parts is a function of the plane of interest, the stance of the subject, and the interface between the subject and the ground. Inherent individual differences and the

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nonlinearity of the system further complicate the issue. Thus the validity of any simplifying assumption is context dependent. The appropriateness of any parameter as a gauge of postural stability is also a function of the testing dynamics. As examples, postural performance can be the transient response to or recovery from a sudden perturbing stimulus, the steady state response to an ongoing stimulation or condition, or even the transient response to an ongoing stimulus condition when some other parameter is suddenly changed.

Since the stability of the body is related to the

position of its center of gravity relative to its base of support, monitoring of this dynamic mathematical point has often been used. This is not an easy task, especially since the location of the center of gravity moves within the body as its parts move relative to each other. Measuring the movement of parts of the body involved with its stabilizing feedback mechanisms has also been employed. The head contains the sensory transducers for the visual, auditory, and vestibular feedback systems, and the rotation of the ankle joint is considered a major source of proprioceptive information. Once the postural measurements have been made, the collected raw data still needs to be collapsed in order for evaluations and conclusions to be extracted. There is generally a lack of uniformity in the literature as to how this analysis is accomplished.

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1.3.2 Previous Postural Measuring Systems



As an example of a simple yet coarse mechanical measure of postural stability, Gonshor and Jones (1980) measured the time a subject was able to stand on a narrow rail. Thus their test is related to movement of the body's center of gravity relative to its interface with the ground. Another relatively simple mechanical method, one which records head position, was the use of a hat with a spring loaded pen pointing upward to draw on a sheet of paper suspended over the head of the swaying subject (K.D. White, personal communication, 1985). This sway pattern on the paper was subsequently scored to evaluate postural stability, a method both tedious and of limited accuracy. Possible methods of scoring are measurement of the maximum radius of the pattern along various orientations, measurement of the total area encompassed by the pattern, and measurement of the total locus of sway as performed by Dornan et al. (1978).- They used a computer and two potentiometric linear displacement transducers connected by spring loaded strings to the sacrum and the greater trochanter of a subject to graphically produce and measure the total locus of sway of a part of the body that roughly approximates its center of gravity. Gantchev et al. (1981) were concerned with anteroposterior sway and used the total locus of sway, or "total way" (sic), only in that direction as the performance parameter. This was accomplished with another variation of a mechanically

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connected transducer as described by Gantchev et al. (1972). A point approximating the center of gravity on a subject's body was connected to a tensiometric lever whose deformations were converted to an electrical signal. However in similar study employing the same apparatus, Gantchev and Koitcheva (1981) used the mean amplitude of sway as the performance parameter. Nashner et al. (1982) measured the anteroposterior sway of a subject's "center of gravity" with a single potentiometric linear displacement transducer connected to the hips with a lightweight rod. The performance parameter was calculated by numerically integrating the rectified sway signal (with steady state offset removed) over the trial interval. Reason et al. (1981) performed the sway signal integration by using a voltage to frequency converter and a digital counter. Vidal et al. (1982) were interested in the effect of a stabilized visual stimulus on body sway in the sagittal plane. This was accomplished by using the output of a single potentiometric linear displacement transducer connected to the subject's head by a lightweight rod to both control the anteroposterior movement of a visual surround and also as a sway measure. A cart upon which the subject was standing was suddenly accelerated and the transient sway response was recorded. The maximum angular pitch of the body was used as a performance parameter, and this was calculated using the potentiometric output signal in conjunction with the assumption that the body acts as a rigid inverted pendulum.

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Others such as Lestienne et al. (1977) connected an angular displacement transducer to the subject's calf to measure anteroposterior ankle rotation, and this was used directly to determine the maximum angular body pitch. Similarly, Soechting and Berthoz (1979) used an angular potentiometer connected by a rod and crank mechanism to a helmet worn by the subject to measure the anteroposterior body pitch angle. Such connected devices introduce the major problem of mechanical loading, which gives the subject positional cues, as well as having limited resolution and range and of being mechanically unidirectional in most cases.

A more sophisticated but relatively expensive

mechanical system is the stabilimeter or force plate as used by Lestienne et al. (1977) and others. The subject stands on a rigid plate mounted on strain gauges and as his center of gravity shifts, the forces exerted on each strain gauge change correspondingly. However, this device only yields quantitative information about movement of the body's center of pressure location (i.e. the position of the ground reaction forces acting on the feet) which is only loosely related to the body's center of gravity location (Koozekanani et al., 1980). This in turn is not totally representative of the body's position since the body generally does not behave as the one link inverted pendulum model as is sometimes assumed (Stockwell et al., 1981). In addition, the mass and mechanical impedances of the stabilimeter limit the upper end of its frequency response,

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and it is inappropriate to use in situations where it is desired to induce controlled acceleration of the body via the feet as an input parameter (Soechting and Berthoz, 1979). In spite of its frequency limitations, Lestienne et al. (1979) and White et al. (1980) chose to examine the stabilimeter data collected in their studies using Fourier transforms. In the former study the power spectral density of anteroposterior sway was presented, and in the latter study the lateral sway data was normalized with respect to individual differences by presenting spectral gains (ratios of power spectral densities of test and baseline conditions). Also in the latter study (one of very few concerned with lateral sway), the subject was instructed to stand on one foot to decrease stability and enhance the effect of visual stimuli.

A system which permits measurement of head, neck, hip and knee movement was described by Booth and Stockwell (1978). Pin lights attached to appropriate parts of the body are detected by a videocamera whose signal is connected to an interface. The interface assigns each light in the videofield an X and Y coordinate value which is fed into a computer for later analysis. Computer based video systems have greater accuracy then mechanical systems, but can be quite costly due to elaborate hardware and software requirements. The fundamental resolution limits of video systems are pixel size and number of pixels per videofield. If the video field must encompass the entire range of

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possible sway then, for commonly available NTSC standard video cameras, approximately 256 x 256 pixels limit the resolution per field. The smallest resolvable movement is therefore about 1/256 of the field extent in the shortest ("video vertical") direction. In the system of measurement described below (in section 2.1) the minimum resolvable movement is more nearly 1/1000 or less of the range of possible movement, a significant refinement. Two such video systems have been presented as doctoral dissertations by Cheng (1974) and Andres (1979).

Another source of data used in determining the effect of stimuli on postural stability is EMG activity of leg muscles. The muscles used in different studies were the hamstrings, the quadriceps, the gastrocnemius, the anterior tibialis, and the soleus. These data have mainly been used in assessing transient performance after a sudden perturbation or change of conditions. Some of the performance parameters extracted from the data are -(a) time to initial response onset, (b) time to peak response, and

(c) the energy of a response during some time interval. Even the same parameters are generally evaluated by different methods (e.g., different signal filtering schemes) in the various studies, a complication in the interpretation of these psychophysiological response measures.

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1.3.3 Previous Stimulus Feedback Systems



Most previous studies employing a visual stimulus

controlled by movement of the subject were concerned with one spatial dimension only. Nashner et al. (1982) had a visual surround which rotated in the sagittal plane about an axis connecting the ankle joints and controlled by the anteroposterior sway orientation of the hips with respect to the ankle joints (as measured by a potentiometric linear displacement transducer). The precision of the visual feedback was quite coarse because of the assumption that the body acts as a one link inverted pendulum. Since there was no compensation for head movements, the feedback gain provided by the apparatus was not a constant. Vidal et al. (1982) avoided this problem by having the anteroposterior displacement of the head (as measured by a potentiometric linear displacement transducer) control the mechanical displacement of a visual surround along a track similarly oriented. However, the timing characteristics of their system were not reported. In a kind of visual pseudo feedback system used by Soechting and Berthoz (1979), the velocity (in a fore-aft direction) of a visual pattern projected on a horizontal surface over the subject's head (the sole visual input due to the use of blinders) was determined by the transient velocity pattern of a cart within which the subject was standing. Thus the movement of the visual stimulus was tightly correlated to the movement

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of the subject's feet but not the subject's eyes (because of the head movements of the subject).- The visual feedback stimulus used by Gantchev and Koitcheva (1981) and Gantchev et al. (1981) was a horizontal line displayed on a monitor positioned 1 m from the subject. The vertical movement of the line was controlled by the anteroposterior sway of the subject (measured at a point approximating the center of gravity of the subject's body). The gain, polarity, and response delay of the vertical movement of the line were independently variable, within limits. Again, actual movements of the head and eyes were neglected in formulating the visual feedback conditions.

In contrast to the above situations, in the Gonshor and Jones (1980) study the movement of the visual feedback stimulus was not limited to a single dimensional component of the subject's movement. Now the stimulus correlation or gain was limited to a single value with sign reversal achieved optically and virtually instantaneously. Unfortunately, the limited visual field forced by the use of prisms plus the crude response measure used in this study limit the generality of their findings. Dove prisms were mounted in goggles so as to produce horizontal inversion of the optical image, which reversed the direction of movement of the retinal image during any head movement in the transverse plane.

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1.3.4 Position Sensor System Overview



The Position Sensor System (PSS) has been developed as an economical yet high resolution tool for measuring body sway in three dimensions, performing mathematical analyses of sway data, and generating visual stimuli to ascertain their contributions to postural stability. It is a vast improvement over other systems to date used to measure postural stability, and should expand the scope of research possibilities as well as being a readily affordable clinical screening tool. The PSS as currently implemented is a multicomputer based system composed of four major subsystems: a Data Acquisition Subsystem (DAS), a Stimulus Control Subsystem (SCS), a Stimulus Projection Subsystem (SPS), and a Data Processing Subsystem (DPS). The DAS and the DPS together can measure and analyze postural stability independent of the stimulus subsystems. Also the SCS can be programmed to generate independently and to control-the projection of visual stimuli by the SPS; else the SPS can function separately given appropriate analog control signals.

The microcomputer based DAS is the hub of the PSS. Its function is to sample continuously the position and orientation of a standing subject's body within a finite volume that is large enough to accommodate the extreme possible limits of postural sway in any direction. It also functions as the "master" control center to run experiments

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and coordinate the operations of the other sub-systems. A unique feature of the DAS is that its operation is based on acoustics. The principle involved is that the distance from a point sound source to a point sound receiver can be determined by measuring the propagation time of a transmitted sound front. A source's position in three dimensional space can generally be ascertained by employing three noncollinearly-fixed receivers. The DAS samples the distances from acoustic sources secured to a subject's body to fixed microphones positioned within the subject's surroundings.

The SCS generates analog waveforms that drive the SPS. Based on a separate microcomputer, it can run independently of the DAS, be synchronized by the DAS, and/or use the raw position data transmitted by the DAS. In the latter case, the SCS computes the subject's position and orientation online, and uses some specified function of the processed data to control the SPS.

The SPS incorporates a vertically oriented cylindrical screen within which the subject stands, and a projector which is positioned along the cylinder's axis of rotation above the subject's head. The projector is a shadowcasting device which projects a vertical grating onto the screen that totally encompasses a properly positioned subject's field of view. The grating moves horizontally across the screen as dictated by the SPS input analog control signal.

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The DPS stores and processes the raw data, and allows for offline file manipulation -to repair data errors. Some of the statistical analyses performed offline on the processed data are position and velocity means and standard deviations, spatial variance and covariance. The Fast Fourier Transform is used to examine and compare the frequency spectra of body sway data collected under different stimulus conditions. The DPS can provide numerical-and graphical outputs to either a monitor or a printer.

The PSS is a powerful, versatile tool which will permit the investigation of many factors involved in postural stability. It has already been used, not only in the present studies, but also in a research project involved with postural stability'during saccadic eye movements (Krantz, 1985), and is presently being used in related projects.





1.4 Proposed Study



It has been demonstrated that visual cues have the

potential of being the dominant or heaviest weighted sensory input, even when they are in conflict with other cues, resulting in postural instability (e.g., Gonshor and Jones, 1980) Yet it has also been shown that when a visual cue is in conflict with vestibular information as an internal

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reference, the visual weighting may be reduced (Nashner, 1982). Nashner (1982) has shown that even when a visual cue is destabilizing, its weighting is also a function of the other inputs to the system. Possibly there are important situational differences between the two studies.

Gonshor and Jones (1980) studied direction reversal of the lateral movements of retinal images while Nashner (1982) studied a stimulus moving in an anteroposterior direction with resulting collinear sways. It is not presently known whether there are separate mechanisms for postural stability in these two planes or what the interactions between them might be. Certainly different skeletal muscles are involved. Also lateral sway in front of an object results in lateral retinal image motion while anteroposterior sway results in a change in the size of the retinal image of the surrounding objects (as well as a possible change in ocular vergence).

Another difference has to do with the visual feedback gain, which can be expressed as the relationship between a subject's movement and the resulting retinal image motion. Normal vision provides negative feedback, defined as having a retinal image feedback gain of minus one. In the Gonshor and Jones (1980) study, the inverting prisms would have produced a gain of plus one (direction reversal to positive feedback) since movement of the subject resulted in an equal but opposite retinal image motion from that expected. In the Nashner (1982) study the stabilized (not environmentally

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stationary) stimulus would have produced a gain of zero, since subject movement results (in principle) in no change in the retinal image. (Since there was no compensation for head movements, the apparatus approximated poorly a gain of zero.)

Previous studies that attempted to vary systematically the gain and phase of the retinal image feedback (Gantchev and Koitcheva, 1981; Gantchev et al, 1981) have suffered from contrived methods to control the (normally uncorrelated) longitudinal retinal image motion by anteroposterior body sway, and this precluded the possibility of distinguishing between positive and negative feedback. In addition, tChe feedback stimuli used only subtended a small fraction of the total visual field (e.g., a video monitor positioned 1 m from the subject).

The present study proposes to quantify the effects of a range of experimentally altered visual feedback gains on postural stability, to clarify issues described above. Postural performances will be expressed as comparative body sway frequency spectra similar to those presented by White et al. (1980). Frequency analyses of sway have seldom been investigated, and when they have, they generally have focused below 1 Hz since that is where most of the sway component spectral energy resides. The common assumption that nothing of interest occurs above 1 Hz will be explored.

The hypothesis is that visual feedback contributes to at least two factors affecting postural stability; namely

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the size of the retinal image motion and the correlation of this motion with the body sway. The interaction of these factors should be revealed by the influence of various altered feedback gains on a subject's stability.

The first factor is related to how the weighting of

retinal image motion may be proportional to the magnitude of the sensory input, so that altered visual feedback gain may disrupt postural stability differently in the presence of larger retinal image excursions ("stimulus magnitude effect").

The second factor is related to how feedback affects

the stability of a system. It is further hypothesized that the postural control system adaptively adjusts some internal feedforward gain characteristic, so as to achieve functionally appropriate body sway performance with the in herent optically determined visual feedback gain. This gain is proportional to the ratio of the magnitudes of retinal image motion to head movement and is assume-d to be negative. Additional parameters that enter into the setting of the internal feedforward gain are (a) the physical characteristics of the body (e.g., mass distribution, muscle tone, etc.), (b) the retinal, neural, and motor activity time delays, (c) the environmental and situational factors the body is normally exposed to (e.g., shoe type, gymnastic training, mountain climbing, etc.), and (d) the internally programmed relative weighting of visual and other sensory inputs.

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Increasing the externally imposed negative feedback

gain might decrease body sway or some frequency components of that sway, depending upon the phase lags introduced by the experimental apparatus. Beyond a certain point, increasing the negative feedback might lead to overcompensating postural movements leading to increased instability. Decreasing the negative feedback but especially introducing positive feedback (direction reversal) should be highly disruptive to the maintenance of balance.

Another consideration involved with visual feedback is the absolute and relative values of the input signal and how each affects stability. If retinal image motion per se is the sole visual feedback input to the system, then for a given body movement, zero retinal image motion opens the loop so that retinal image motion in the direction normally encountered constitutes negative feedback and in the other direction constitutes positive feedback. Therefore, for a given body movement, relatively small retinal image motions in these opposite directions may result in profoundly different postural performances (notwithstanding reduced visual weighting in both cases due to the stimulus magnitude effect).

On the other hand, the system is "used to" a particular value of negative feedback gain. If this value behaves like a set or transition point, then a small change in gain from above to below this value may result in a greater variation

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in postural performance than would be found with a similar change in feedback gain about a different quiescent point.

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CHAPTER 2
POSITION SENSOR SYSTEM DESIGN AND DEVELOPMENT





Overall design of the Position Sensor System (PSS) has been described in the context of previous measuring devices and of the proposed study in section 1.3.4. The complete PSS consists of four subsystems, whose flow of control generally presumes that the Data Acquisition Subsystem (DAS) is the system "master" and that the other subsystems act as its peripherals. The Data Processing Subsystem (DPS; a TERAK 8510a and 8512 microcomputer with disk drives) simply receives serial data transmissions for mass storage and offline analyses. The Stimulus Control Subsystem (SCS) can stand alone, but otherwise relies upon online data transmitted via a parallel link to the DAS, in order to control the Stimulus Projection Subsystem (SPS).





2.1 Data Acquisition Subsystem



The DAS is designed to ascertain the distances from acoustic sources secured to a subject's body to fixed microphones positioned around the subject. It is 33

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predominantly based on hardware component sections that are controlled by a small microcomputer which also functions as the main control center for the overall PSS. Preliminary versions of the DAS, presented in two previous papers (Shuman, 1981a and Shuman 1981b), demonstrated that the apparatus was capable of achieving a relative source to receiver distance resolution of better than 1 mm over more than a 1 m range.

In its present implementation the DAS is capable of sampling distances at a 50 Hz rate. It generates pulses which are gated to the acoustic sources in sequential order to produce click sounds. Each of these pulses also starts all the digital timers, one dedicated to each a microphone. When a click sound is received by a microphone, its timer is stopped, and after the click sound has been received by all the microphones, the microcomputer reads and resets all the timers. Acoustic source identification and synchronization is achieved by click pulse width encoding and detec'fion. If operational errors are not detected, the DAS transmits the collected raw data online to storage for offline processing, and if appropriate, to the SCS for a stimulus position update.

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2.1.1 DAS Hardware



The DAS hardware, represented in the PSS block diagram in Figure 1, is composed of three main component sections centered around the position microcomputer (see section

1.3.4 for a general system overview). In this depiction, the sound generation component consists of an acoustic source driver circuit and 1 to M sound transducers. The sound reception component consists of 1 to N microphone/detection circuits which are connected to the computer via the timer interface circuit component. This component contains 1 to N timers, a square wave generator, test control and synchronization circuitry.

A subject could theoretically wea r any number of

miniature acoustic sources, each determining the location of that part of the body to which it is attached. In reality, any obstacle in the path between an acoustic source and a microphone, such as the subject's body, results in -a shadowing effect which alters (increases) their relative distance reading. In addition, acoustic sources and microphones have nonuniform directional characteristics which become more problematic at higher frequencies. This necessitates employing additional appropriately aimed fixed microphones around the subject so that each acoustic source has a clear path to a least three microphones for any possible position of the subject. Also each source to microphone path needs to be within some specified angle from

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DAS DPS

FULL BUS I I
S Ii, MASS I
STORAGE
I POSITION I I DEVICE
TIMER MICRO- I -.
CLOCK COMPUTER INTEPRUPTI---------- SCS
DRIV EN STIMULUS I
SQUARE YN TEST MICRO- I
WAVE C TIMER 1 TIMER N PAR LLE COMPUTER
GENERATOR DETECTOR CONTROL L
A AI FULL BUS
START STOP I
L ID/A START STOP I I
ACOUSTIC BEGIN HALT SCREEN i CONVERTER I
SOURCE SUMMED CLICK PULSES L.-
DRIVER STATIONARY DRIVER
1 ** M MICROPHONE/ AMPLIFIER
DETECTOR


I GALVANOMETER/
PROJECTOR

SPS

Figure 1. Position Sensor System Component Sections. These sections are the Data
Acquisition Subsystem (DAS), the Stimulus Control Subsystem (SCS), the Stimulus
Projection Subsystem (SPS), and the Data Processing Subsystem (DPS).,

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the central axis of the source, this angle being a function of the source's dispersion characteristic and of the frequency spectrum of the employed sound. It is then the task of software, using error detection techniques, to select the appropriate microphones to use in the localization of each acoustic source.

For this study, the determination of the position and orientation in the transverse plane of the head of a standing human subject is used as the measure of postural stability and in the derivation of the visual stimulus control signal. This is accomplished by -the use of two sources attached to the head and positioned along a

-transverse plane. In order to achieve adequate orientational resolution and to be outside of the subject's field of vision, -the sources are positioned 40 cm apart on opposite sides of the head. This is implemented by I fastening them to the ends of-a slat (constituting the "headpiece") which is attached to a hat consisting of the plastic webbing taken from the inside of a construction hard hat. The webbing can be adjusted to fit securely to eliminate relative movement between the sources and the subject's head. Four microphones are positioned at the vertices of a square of length 100 cm mounted horizontally 71-8" above the floor. This square, bolted to the ceiling and referred to as the system overhead frame, is constructed from aluminum L stock with flat aluminum diagonal crosspieces to maintain squareness and support SPS projector

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and screen. To collect data, a subject is initially positioned under the center of the square and facing parallel to two of its sides. The acoustic sources point upward and the microphones are aimed inward towards the center of the square and downward at a 45 degree angle to the plane of the square. This configuration works within the limitations of the directional characteristics of the acoustic sources and the microphones for any expected body

sway of the subject.

The volume of space within which acoustic sources could theoretically be localized is anywhere between the plane of the suspended.square and the floor. With the practical constraints of the amplitude of an acoustic source output, the sensitivity of -the microphones, and noise considerations, it was necessary to define a volume of space within which the acoustic sources could be expected to be found. A decision was made to impose the limitation that the distance from the top of a subject's head (where the acoustic sources are positioned) to the floor be within the range of 5' to 61-4". It was empirically determined that the maximum a subject's head could move in any direction along the transverse plane during body sway was 30 cm. This information was used in calibration and characterization of the DAS as will later be seen.

The acoustic sources are common miniature earplug speakers modified to broaden their sound dispersion characteristic by cutting off the protruding plastic that

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would normally fit in -the ear. Each source employs an eight ohm voice coil to move a small ferrous diaphragm and the sound is emitted through the 7 mm diameter hole left after modifying its plastic case. Under a worst case condition of a subject's head being 6'-4" above the floor and swaying 30 cm away from a microphone, the maximum angle between the central axis of the distal source and a line connecting this source/microphone pair is 70 degrees. Using data previously presented (Shuman, 1981b), this results in a maximum increase of 3 mm in the sampled distance beyond the value found when the source is pointed directly towards the microphone. The relative error between consecutive samples for any possible body sway is substantially less.

The sources are powered by the acoustic source driver circuit represented in Figure 2. The complete schematic diagram for the present implementation was previously shown in Shuman, 1981b. The driver generates pulses which are gated sequentially to the appropriate sources to pr-oduce click sounds. The circuit also generates a timer control signal (summed click pulses) to notify the timer circuits of each click sound's transmission. In the initial design (Shuman, 1981a), the battery powered driver circuit was to be worn by the subject and the timer control signal would be relayed by an FM transmitter/receiver pair to the timer circuits. This was to insure that proprioceptive positional clues would not result from wires connecting the subject to any stationary object. In the present implementation, a

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601 80
sec sec


7O 70/S
(~ eq sec
I 0 1
I i I I I
t J-I It


SYNC DETECTOR 1 1


Figure 2. Acoustic Source Driver and Synchronization
Waveforms. Acoustic source identities are encoded synchronization. The acoustic source driver pulse


Circuit Components with Operational in the click pulse widths for has a slow decay to reduce ringing.


SQUARE WAVE INPUT


POSITION
MICROCOMPUTER

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stationary driver circuit is connected to the acoustic sources, by fine wires dangling from the end of a light spring over the head of the subject. This is found to also adequately eliminate proprioceptive clues and obviates the use of the FM transmitter/receiver pair. For safety considera tions, the driver circuit is still battery powered so that the acoustic sources attached to the subject are never even indirectly connected to the 120 volt power line in the laboratory. The batteries in the driver circuit (two

9 volt transistor batteries) are automatically recharged whenever the main power to the PSS is turned off.

The acoustic source driver circuit can operate in three possible modes: a free running sequential order mode for normal use and two manual modes for testing and calibration (a sequential order mode and a single acoustic source repetition mode). The free running mode requires a square wave input signal which can be generated by a self contained oscillator whose frequency is controlled by a precision variable resistor. In the present implementation, the square wave input is more precisely generated and controlled by the timer interface circuit under software control. The acoustic source pulses are at the oscillator frequency and so the DAS sampling frequency is equal to the oscillator frequency divided by the number of acoustic sources. The manual modes use a mechanical switch and a debouncing circuit to generate single pulses.

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Each pulse of the square wave input signal train is sequentially gated to the appropriate power circuit dedicated to a particular acoustic source. A power circuit consists of a EGC 186A power transistor whose base is driven by a dedicated one shot. In order to create a sharp click sound (i.e., a fast rise time sound wavefront), the one shot output biases the power transistor into saturation which in turn supplies the acoustic source with a fast rise time high current pulse (approximately 2 amps) The diode across the inductive voice coil of the speaker reduces the voltage induced when the transistor is turned off. It was empirically determined that a one shot pulse width between approximately 50 to 80 jisecs results in a maximum amplitude microphone output for the transducers used. This is apparently due to the resonant frequency of the microphone which rings at about 8 kI-z since half of its resonant period is approximately equal to the mean of the above one shot pulse width range. Such a short pulse also does not overheat or burn out the acoustic source for the duty cycles involved (less than 0.25% with a 25 Hz sampling frequency).It was discovered that the rectangular current pulse resulted in the click sound persisting for a long time after the pulse ended, due in part to the resonant oscillations of the speaker's diaphra gm. This in turn reduced the maximum sampling frequency of the DAS. The problem was partially solved by slowly returning the speaker's diaphragm to its rest position. This was accomplished by reshaping the

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43

rectangular base drive of the power transistor to be more like a sawtooth. An RC circuit providing a 2 msec decay time constant was empirically found to permit the highest click rate frequency.

The outputs of all the one shots are summed to provide the timer control signal previously mentioned. In addition, this composite signal is used by the position microcomputer to achieve synchronization with the acoustic sources by means of the sync detector section of the timer interface circuit. As shown in Figure 2, the one shot output is about 60 vIsec for acoustic source 1 and about 80 lisec for all the other acoustic sources. The composite signal, shown as waveform A, triggers the sync detector one shot which has an output duration of about 70 visec, shown as waveform B. The sync detector latch, which is reset by the position microcomputer at the leading edge of each acoustic source one shot output, is set by a latch pulse (waveform C) which is only generated when acoustic source 1 is activated. The position microcomputer reads the latch to ascertain the beginning of a' sequence of acoustic clicks and also to check that the number of clicks in each sequence (corresponding to a complete sample) is correct, as is discussed further in section 2.1.3 on the DAS software.

The function of each of the microphone/detection

circuits is to indicate precisely the time of reception of an acoustic click transmitted from anywhere within the volume of space that the subject's head could reasonably be

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44

located. Each circuit, as portrayed in Figure 3, is self contained in a shielded metal-box. The microphone sound transducer is a miniature piezoelectric crystal element which produces a ringing response at its resonant frequency (approximately 8 kHz) when the click sound pressure wave front impinges on it. This ringing is first amplified by a differential input 40 dB preamplifier utilizing an LM725 operational amplifier with external frequency compensation. This op amp was chosen because of its wide bandwidth and good noise performance as well as its high common mode rejection ratio (CMRR) of 120 dB. The common mode rejection (CMR) of the circuit is maximized by adjusting RCOM. A second stage of about 50 dB gain employs an externally compensated LM725 op amp in an inverting amplifier configuration to bring the signal level up for detection. The two stages are directly coupled and their net offset voltage, as measured at the output of the second stage, is nulled out by adjusting ROFF in order to maximize the dynamic range of the pair. The signal is then capacitively coupled (to remove any dc component due to drift) to a threshold detector consisting of an LM741 op amp in an open loop configuration with a threshold level set by RTH. The output of the detector is a pulse which goes from about

-10.4 V to +10.8 V whenever the signal crosses the threshold level. A common emitter transistor converts the pulse to appropriate logic levels so as to act as a stop pulse for the appropriate timer. Because of the finite slew rate of

..





























TRANSDUCER Radio Shack 273-06.


(Threshold Level Adj.)


100K


-1 2V


5K RCOM


3rd

THRESHOLD LEVEL @AMPLIFIER OUTPUT-1s INITIAL RECEPTION I
OF "CLICK" 2nd1




+12V I


@ DETEC TOR OUTPUT 12

Figure 3. Microphone/Detector Circuitry with Operational Waveforms. The threshold level
is set to detect the third peak of the microphones ringing response to the click sound
produced by an acoustic source positioned within the operational volume of the DAS.


+1 2V


) ))


-1 2V

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the detector op amp, its output takes almost 30 4sec to swing from its negative to positive saturation values. This characteristic is capitalized upon in the performance of some low pass filtering which reduces false detection by noise spikes. A 6.2 V zener diode is incorporated into the base circuit of the transistor so that true detection requires the op amp output to exceed about +6.9 V or more than 75% of its possible voltage excursion. Therefore, detection requires the input signal to exceed the threshold level for almost 23 jisec.

The initial ringing response to a click sound wave

front at the input of the threshold detector, as shown in Figure 3, is a growing sinusoid whose peak amplitudes are a function of the position of an acoustic source relative to the microphone element. The threshold level should be set high enough to eliminate false triggering due to electrical and unavoidable audible noise and low enough to detect the click sound when the acoustic source is at its expected worst case distance and orientation relative to the microphone element. Another consideration, previously alluded to during the discussion of the acoustic sources' driver circuits, is the effect of the threshold level on the maximum sampling frequency of the DAS. The persistance of the ringing response, which is a function of the click sound waveform. as well as the microphone element characteristic, prohibits the transmission of the subsequent click sound until the ringing has decayed below the threshold level.

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47

Once below this level, a sizable ringing amplitude might still alter the detection time of the contiguous click sound as a result of constructive or destructive interference. This is one source of error which affects the accuracy of the DAS (discussed in section 2.1.,4). An empirical study was performed to determine which peak of the growing sinusoid should be detected for an optimal performance range. Earlier peaks provide a truer indication of the click sound wave front arrival and fluctuations in the ringing waveform introduce less error, but the larger amplitudes of later peaks allow for a higher threshold level. However, beyond the second peak, false detection by a previous peak can easily occur when an acoustic source is close to a microphone. A figure of merit for these later peaks is the amplitude ratio of a peak with the preceding peak of same polarity, and this was greatest for the third peak. Within the volume of space of interest, the third peak minimum amplitude was 0.88 V and the first pea-k maximum amplitude was 0.27 V. Based on the discussed tradeoffs, a

-threshold level of 0.7 V was selected. The polarities of the acoustic sources (actually connected to the driver circuits via polarity reversing switches since the polarities of the miniature earplug connectors were found to be random), microphone elements and threshold levels were chosen to detect the third peak.

The timer interface circuit is entirely digital and could be implemented in a variety of ways depending upon

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48

which microcomputer is chosen for the DAS to be centered around. The present implementation, discussed in detail in Shuman, 1981b, uses a modified Ohio Scientific Challenger 1P 8K microcomputer based on a 6502 processor running at 2 MHz. The timer interface circuit is composed of a Synertek SY6522A Versatile Interface Adapter (VIA) dedicated to each microphone/detection circuit, supporting TTL chips, and buffers for the computer's address bus. The VIA's "Timer 2" 16 bit timers count pulses from gated 1 Mhz signals derived from the microcomputer's internal crystal clock giving a detection digitizing resolution of 1 jisec. These signal gates are opened synchronously by the summed click pulses output of the acoustic source driver and are closed by the first output pulse of its dedicated microphone/detection circuit. Using hardware timing permits greater accuracy in measuring these asynchronous events. Software controls the non time-critical functions of initializing and reading of the timers. Modifications to the timer interface circuit since the description presented by Shuman (1981b) are the inclusion of test control, the square wave signal generator, and the parallel link. Test control consists of begin and halt mechanical grounding switches (pulled up for noise protection) interfaced to the computer by port lines PB4 and PB3 on VIAl (the VIA dedicated to microphone/detector 1 or "1mic 1") and monitored by software. The square wave generator utilizes "Timer 1" on VIAl in its free-run mode which is set to frequency, started, and stopped under

..







49

software control. The output of this generator timer, on PB7, is stepped down to the desired range of frequencies for the acoustic source driver by a TTL 7493 divide by 16 chip. The parallel link, which transmits the microphone dedicated timers' readings to the stimulus microcomputer, utilizes a byte wide port (PAO-PA7) on VIA2 for data and its two associated control lines (CA1 and CA2) for handshaking. The port is connected, with a one to one pin correspondence, to an equivalent VIA port in the SCS. The control lines are cross connected to the VIA control lines from the SCS (input control line CA1 on VIA2 to output control line CA2 from the SCS VIA and vice versa). The sync detector, discussed previously, is also part of the timer interface circuit with its latch reset and read by VIA1 under software control.





2.1.2 DAS Geometric Analysis



The following geometric analysis, although not directly performed or used by the DAS, is presented at this time to clarify how the DAS works in conjunction with the rest of the PSS to fulfill its role in measuring postural stability. The mathematical results of this discussion are actually utilized in the data analysis performed by the SCS and the DPS.

If the distance from a movable point sound source to a fixed point sound receiver is ascertained, then the source

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50

is known to be located somewhere on the surface of a sphere centered about the receiver with a radius equal to that distance. If the distance to a second receiver is known, then the source's position is somewhere along the intersection of the two spheres, which is a circle whose axis of rotation is the line connecting the two receivers. If the distance to a third receiver not on line with the other two is known, then the source is at an intersection of this new sphere with the previous circle, which is two points equidistant from and on opposite sides of the plane defined by the three receivers. If it is known which side of the plane the source is on, then the location of the source in three dimensional space relative to the receivers is established.

For this study, -the determination of the position and orientation of a subject's head along a transverse plane, which involves two translational and one rotational degrees of freedom, is deemed sufficient (Krantz, 1985). This can be ascertained by minimally employing two acoustic sources attached to the head along a transverse plane. An unrestrained head can move with all three translational and three rotational degrees of freedom. With the two sources fastened on opposite sides of the head, all these degrees of freedom can be resolved with the exception of rotation about a line connecting the two sources (like nodding "yes"). However, during typical sway, a body does not lean beyond an amount that would displace its center of gravity beyond the

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51

support base of its feet. Therefore, the up and down motion of the head can be considered a second order effect, and rotations within the sagittal and coronal planes yield little additional information beyond that obtained from head translations in the transverse plane. In addition, within the context of this study employing a vertical grid stimulus constrained to moving laterally around a cylindrical screen, information about head movement involving these other degrees of freedom could not, in any event, have any effect on the stimulus movement.

Figure 4 presents a graphical depiction of the

geometric relationships between the two acoustic sources and four microphone/detectors projected on to a transverse plane. The subject is standing at the intersection of lines Li and L2 looking at a point (Yp,Xp) on the cylindrical screen. The two acoustic sources, Sp 1 and Sp 2, are positioned on opposite sides of the head at the ends of line Li. The four microphone/detectors, Mic 1 through Mic 4, are positioned at the vertices of a square that is over the head of the subject, thus removing any ambiguity as to which side of the receiver plane the source is on (as discussed above in this section). The distances, D1 through D8, correspond to the eight possible speaker-microphone (sp-mic) pair combinations. These distances are used to calculate the x and Y coordinates of Sp 1 and Sp 2 using the following equation derived from the Pythagorean theorem in Krantz (1985):

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Figure 4. PSS Geometry: Head Localization and Stimulus
Angle Determination. The subject's head is located at
the intersection of line LI (connecting the acoustic
sources) and line L2 (a segment of which is the subject's
line of sight). The distances from acoustic sources to
microphones (D1 through D8) are used to calculate the
acoustic sources' coordinates which defines the subject's
location and orientation. The intersection of the
subject's line of sight with the cylindrical screen is used to calculate the stimulus visual feedback angle E).

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53

(1) CV =((Dist A) 2-. (Dist B) 2) / (2L)

where CV is a coordinate value of an acoustic source, Dist A and Dist B are the distances from this acoustic source to two microphone/detectors lying on a line parallel to the axis that is the same as the desired coordinate, and L is the distance between those two microphone/detectors (empirically found to be 100.2 cm) Thus, in conformity with the above discussion, the determination of the location of an acoustic source in a transverse plane requires the employment of three microphone/detectors. With the four available microphone/detectors, each of the four coordinate values can be calculated using two different distance pairs, and this redundancy allows for a certain degree of error correction. The choice of which distance pair to try first is based on the practical consideration of minimizing potential interferences. For the X coordinates, the determining factor is possible head shadowing, and for the Y coordinates, it is possible ambient noise coming frf6m behind the subject (due to the location and orientation of the experimental setup relative to the experimenter and the rest of the laboratory) Table 1 presents the resulting default and alternative coordinate determinants. For example, the default implementation of equation (1) for the Y coordinate of Sp 1 is

(2) Y1 = (D2) 2 (Dl) 2) M2)

and the alternative implementation is

(3) Y1 =((D3)2 (D4)2)/(2L)

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54

Table 1
Coordinate Determinants



Speaker Default Alternative
Coordinate Distances Distances
Y1 D2-DI D3-D4

Xl D4-D1 D3-D2

Y2 D7-D8 D6-D5

X2 D8-D5 D7-D6



A raw position datum for a sp-mic pair is a 16 bit

integer corresponding to the number of (approximately) 1 Mhz clock cycles that occurred between the beginning of the acoustic source driver pulse and the detection of the third peak of the microphone/detector's ringing response (see section 2.1.1). The expression of the relationship between this number and the distance from the acoustic source to the microphone detector is

(4) C = mD + b

where C is the number of clock cycles, D is the distance, m is a factor related to the speed of sound in air, and b is a constant resulting from the delays involved with the transmission and the detection of the sound front. It was empirically determined that for all the sp-mic pairs

m = 28.46 cycles/mm with a variance of 0.0006

and b = 175.5 cycles with a variance of 31.0

which is reasonable since m is a physical constant and b is a function of variability in electronic components.

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55

Combining the above equations and empirical measures, the expression for a coordinate value in mm is

(5) CV = ((CA)2 (CB)2 + 351(CB CA))/16232

where CA and CB are the sp-mic pair raw position data measured in clock cycles, using the pair distances described in Table 1.





2.1.3 DAS Software



The DAS software is an online system that manages the

execution of experimental trials, which in turn involves the collection and transmission of raw position data as it is generated. The raw datum for each sp-mic pair is a 2 byte number read from the timer dedicated to that particular microphone/detector. In this implementation, a complete sample is composed of two groups (corresponding to the two acoustic sources) of 8 bytes (corresponding to the four microphone/detectors) for -a total of 16 bytes. DAS management involves control of the sampling rate, number of samples per trial, and initiation of a trial. In addition, the program checks and corrects for loss of acoustic source number synchronization and overflow conditions which occur if the input data rate exceeds the output rate. It is designed to run in conjunction with the previously described DAS hardware (section 2.1.1) centered around a 6502 based modified Ohio Scientific Challenger CIP microcomputer

..









(henceforth referred to as C2). In order to perform its function at maximum speed, the program runs at a machine language level uhder the control of a BASIC program which also performs offline tasks and acts as a user interface. The complete program fits well within the 8K of user RAM, with less than 350 bytes allocated to the machine language program and associated buffer locations.

There are presently several different versions of this software in each of two groups. The various BASIC versions provide for different experimental designs and for either a software or hardware controlled square wave generator input to the acoustic source driver. The two groups have to do with the machine language portions of the programs. Group 1 is optimized for the highest possible sample rate, with transmission of the raw data via an RS-232 4800 baud serial link to a mass storage device (the DPS) for offline analysis. This is accomplished by transmission of the collected raw data from the previous sample during the software idle periods between transmission and reception of the click sounds (typically 2 to 4 msec). Group 1 programs can Operate at a 50 Hz click rate or a 25 Hz sample rate with a two acoustic source implementation. Group 2 programs, one of which was used in this study, are designed for the case in which the motion of the subject can affect the stimulus motion. Therefore the raw data are transmitted to the stimulus microcomputer (henceforth referred to as Cl) via a byte wide parallel data link as well as to the DPS.

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57

In this case, the delay until transmission of the raw data is crucial and so this delay is minimized at the expense of reducing the maximum click rate to 20 Hz or a 10 Hz sample rate. In order to avoid having the position microcomputer

(C2) wait for the stimulus microcomputer's (Cl) need for more data, any attempted transmission by C2 on the parallel link generates an interrupt on C1.

The BASIC program used in this study, CTRL.BAS, and the assembled form of its group 2 machine language program, CTRL.MLP, along with detailed documentation and a memory map of the system, are all included in section A in the Appendix. Operation of the DAS software begins with CTRL.BAS poking (loading) the machine language program into memory, and then initializing the timer interface circuit and locations in C2's RAM involved with the operation of CTRL.MLP. Of major interest are the sync memory location which keeps track of which acoustic source click sound is next expected, the sample counter which monitors the duration of a trial, and the data storage block (DSB) which is an 8 byte buffer used for temporary storage of each data group before transmission via the serial and parallel data links. The timer interface circuit initialization includes the (a) set up the parallel link to interrupt C1 when C2 is ready to transmit data from the DSB, (b) notify Cl when valid data is on the link, and (c) wait until Cl acknowledges receiving each byte before sending the next one. If acknowledgement is not received within certain time

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period (the time until the next click sound is transmitted), a flag is set and transmission via the parallel link is aborted. The raw timer data are stored in the DSB prior to transmission in order to have a briefer interrupt of C2 than would be possible if the individual timers were read and written directly to the parallel link.

After initialization is completed, the user is asked to enter the desired sampling rate and number of samples per trial. A prompt on the monitor asks the user to turn on the battery powered acoustic source driver, to check that the stimulus computer is ready, and to press the BEGIN switch. Pressing the switch turns on the square wave generator which starts the click sounds and CTRL.MLP is entered. An overview of CTRL.MLP is shown in the flowchart in Figure 5. The system is prepared to expect a click sound from Sp 1 by setting the sync memory location and the countdown timers are initialized (to $FFFF, where $ indicates an hexidecimal number) in preparation for counting clock pulses. The HALT switch used to abort manually and the sample counter which terminates a trial if it reaches the user specified number of samples per trial are checked. If termination is

indicated, a termination routine is entered which begins by loading the DSB with a termination code (8 bytes of $FF). A delay insuring that Cl is ready to receive data (Cl operation is discussed in section 2.2.3) is accomplished by

waiting for the next click to be transmitted and detected by Mic 1. The termination code in the DSB is transmitted a

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The Data Storage Block (DSB) C Enter from BASIC accumulates all the timer data for each click prior to transmission to the Stimulus Computer (Cl) r
and Mass Storage. Initialize for Spl


Figure 5. DAS Software Flowchart: Online Operation.
CTRL.MLP manages the detector timers, acoustic source
synchronization, and timer data transmission.

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byte at a time to C1 via the parallel link, then serially to mass storage, and then again to C1. C1 may need to receive the termination code twice before recognizing termination by C2 (depending upon the state of Cl at the time of interrupt), and the two interrupts of Cl need to be separated by a time period provided by the transmission to the DPS (discussed further in section 2.2.3). The sample counter is updated, then the program returns to CTRL.BAS which turns off the square wave generator, thus stopping the clicks sounds, and displays the number of samples in the trial on the monitor. After a pause, CTRL.BAS is ready for the next trial and again prompts the user to turn on the acoustic source driver and check that Cl is ready. The sampling rate and number of samples per trial can only be specified before entering the first trial. If the BEGIN switch is pressed before the acoustic source driver is turned on, a message to that effect is displayed on the monitor and, after a pause, CTRL.BAS is again ready for the next trial.

If a termination (manual abort or sample count reached) was not indicated during the running of CTRL.MLP, it then waits for a click sound (from Sp 1 if CTRL.MLP was just entered) to be transmitted. Upon transmission, which starts the timers counting (purely a hardware function), CTRL.MLP clears the sync detector latch and waits for Mic 1 to detect the click sound. Upon detection, which stops the Mic 1 timer (again a hardware function), CTRL.MLP performs a sync

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check by comparing the expected acoustic source identity (stored in the sync memory location) with the actual acoustic source identity (as read from the sync detector latch). If the sync check is good, the 2 byte datum from the Mic 1 timer is stored in the DSB and the program checks/waits for Mic 2 to detect the same click sound (which it may have already). When it does, the datum from the Mic

2 timer is stored in the DSB and the same procedure is followed for Mics 3 and 4. The sync check is only made one time for each click sound, and that is after its detection by Mic 1. Once all the raw timer data are stored in the DSB, its contents are transmitted to Cl via the parallel link. If data transmission is not successful, as evaluated by the handshaking, the termination routine is entered. If data transmission is successful, the DSB is then also transmitted to the DPS via the serial link, the sample counter is updated, and the sync memory location is set for the next acoustic source. At this point, a check is made to see if the next click sound has already been transmitted. If it has not, CTRL.MLP loops back to prepare the timers for the next click sound and the program continues. If the click has been transmitted then CTRL.MLP has fallen behind (an overflow condition), and the program returns to CTRL.BAS which displays a message to that effect on the monitor. After a pause, CTRL.BAS is again ready for the next trial. Such overflow can be caused by too fast a sampling rate, by missed detection of a click sound by one of the microphones,

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62

or by excessive acoustic source to microphone/detector distance.

If sync check fails then CTRL.MLP increments a sync error counter displayed on the monitor and loads the DSB with the sync error code (8 bytes of $00). If a click sound from Sp 1 was expected but was received from Sp 2, then the sync error code is sent to the DPS twice and the sample counter is updated. This fills a complete record in mass storage so that it has an indication of the sync error and is also prepared next to receive timer data corresponding to Sp 1. Nothing is sent to Cl so that the stimulus position is not updated and Cl is still expecting timer data corresponding to Sp 1. The program then continues by waiting for a click sound to be transmitted, with the expectation that it will be from Sp 1. If the sync error occurred when a click sound from Sp 2 was expected but was received from Sp 1, then the sync error code is sent to Cl. This aborts the next stimulus update even though va-lid timer data corresponding to Sp 1 is currently held by Cl (see section 2.2.3), and leaves Cl expecting timer data corresponding to Sp 1. Under this sync error status, if data transmission to Cl is unsuccessful, then the termination routine is entered. If data transmission is successful, then the sync error code is then sent to the DPS. This completes the partially filled record in mass storage so that it has an indication of the sync error and is also prepared to next receive timer data corresponding to

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63

Sp 1. The sample counter is then updated. Now C1 and mass storage are expecting timer data corresponding to Sp 1 so that the next click sound needs to be ignored. After all of the mics have detected this next click sound and all timers stop, the program loops back to set the sync memory location for Sp 1 and continues as previously described.





2.1.4 DAS Characterization



To fully and accurately characterize the DAS (and later the SCS), it was necessary to be able to translate and rotate the headpiece (the two acoustic sources attached to the supporting slat) over the DAS operational range with an accuracy substantially greater than that of the DAS. In order to accomplish this task, the Calibrated Mechanical Transport System (CMTS) was designed and assembled (described in section B in the Appendix).

The DAS, whose actual output is timer counts

corresponding to distances between microphone/detectors and the two acoustic sources, was characterized based on the processed data output of the offline DPS resulting from discrete tests. For each trial, the DPS calculated the means and standard deviations of (a) the Y and X coordinates of the midpoint of a line (LI in Figure 4) connecting the acoustic sources, corresponding to the location of the center of the headpiece, and of (b) the rotational

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64

coordinate of a line (L2 in Figure 4) normal to line Li, corresponding to the orientation of the headpiece. Thirty two samples (determinations of the coordinate values) were made for each test measurement.

The DAS was first checked for resolution (output consistency) with the headpiece positioned at a single location. A similar approach, discussed in section D.6 in the Appendix, was used in designing the simulation of the stimulus jitter introduced by the variability of the raw position data. The data distribution used in the simulation, although not repeated here, can be considered as additional characterization of the DAS.

With the CMTS adjusted to give nominal Y, X and orientation coordinate positions of (0,0) mm and 0' respectively (graphically displayed in Figure 4), four tests were conducted with the resulting data shown in Table 2. Within the short time span of a single characterization trial (3.2 sec), the standard deviations of the position means primarily reflect experimental uncertainties and noise in the system rather than drift. The means of these standard deviations are referred to in the table as intertrial means of intratrial standard deviations. In the first test, 32 trials were performed in quick succession. Even so, it is seen that the position means do drift slightly as indicated by the larger standard deviations of these means, which are referred to as intertrial standard deviations of intratrial means. In the second test, the

..







65

CMTS was checked for confidence of position repeatability by moving the headpiece and then returning it to the same position (as indicated by the CMTS vernier dials) before each of 32 trials. The results corroborate the accuracy of the CMTS by showing a maximum standard deviation of position means increase of 0.04 mm beyond that found in the first test. The third test further investigated position data fluctuations due to drift over 25 trials. In this test the PSS was powered down for awhile after each of the first two groups of 5 trials and then the PSS was allowed to idle with power on for an hour after each of the second two groups of

5 trials. The results show a substantial increase in the standard deviations of the position means. The fourLt-h test examined the influence of acoustic source use on drift and involved transmitting 2000 clicks between each group of 5 trials for a total of 15 trials. The results of this test indicate that acoustic source usage does not exert a strong influence on drift.

The next series of tests characterizes the DAS for headpiece position data accuracy over a portion of the system's operational range with the use of the CMTS. Of interest is not only the accuracy of the absolute coordinate values but also the accuracy of changes in the coordinate values resulting from small positional perturbations (indicating relative position accuracy) over a range of nominal positions. The results of 5 tests are summarized as error means and standard deviations in Table 3. In each

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66

test the absolute position data errors are calculated by using the line which best fits the data points as found with linear regression analysis. The errors found with lateral (along the X axis) translation are somewhat affected by headpiece orientation and are as much as twice those found with diagonal (along the -450 line) and anteroposterior (along the Y axis) translation. The results also indicate that perhaps more than half of the magnitude of these errors can be attributed to the DAS fixed position resolution limitations previously presented.



Table 2
DAS Accuracy with a Stationary Subject


Parameter Y Axis X Axis Rotation
(mm) (mm) (deg)

Test 1 Rapid succession 32 trials
Intertrial mean of intratrial S.Ds. 0.25 0.32 0.07 Intertrial S.D. of intratrial means 0.27 0.43 0.08

Test 2 Subject moved and returned 32 trials
Intertrial mean of intratrial S.Ds. 0.24 0.33 0.07 Intertrial S.D. of intratrial means 0.31 0.45 0.08

Test 3 System turned off and on 25 trails
Intertrial mean of intratrial S.Ds. 0.29 0.33 0.08 Intertrial S.D. of intratrial means 0.54 0.50 0.12

Test 4 Extensive source operation 15 trials
Intertrial mean of intratrial S.Ds. 0.25 0.30 0.07 Intertrial S.D. of intratrial means 0.22 0.40 0.07

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67

Table 3
DAS Operational Range Accuracy


Test

Rotation
about
(0,0)

Translate along X axis w/ 00 rot.

Translate along X axis w/ -430 rot.

Translate along -450 w/ 00 rot.

Translate along Y axis w/ 00 rot.


Ranqe

-460
to
450a

-531 mm
to
0 mmb

-340 mm
to
0 mmb

-20 mm
to
435 mmc

-147 mm
to
312 mmc


Absolute Position Err Mean Err S.D.
0.200 0.150



0.9 mm 0.7 mm 0.9 mm 0.5 mm 0.4 mm 0.2 mm 0.5 mm 0.2 mm


Relative Position Err Mean Err S.D.
0.110 0.090



0.6 mm 0.4 mm 0.4 mm 0.4 mm 0.3 mm 0.3 mm 0.4 mm 0.4 mm


a) Data point intervals are 60 with 0.30
relative position measurements.
b) Data point intervals are 38.1 mm with
for relative position measurements.
c) Data point intervals are 57.2 mm with
for relative position measurements.


perturbations for 2 mm perturbations 2 mm perturbations


The speed of the DAS, alluded to in the software

description (section 2.1.3), and other factors affecting the performance of this implementation, are discussed among conclusions regarding the PSS in section 5.1.1.

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2.2 Stimulus Control Subsystem



The Stimulus Control Subsystem (SCS) is designed to

generate analog waveforms that drive the Stimulus Projection Subsystem. The SCS is predominantly based on software and, in the implementation discussed here, performs extensive machine language level processing in generating these waveforms as a function of the raw position data it receives from the DAS.





2.2.1 SCS Hardware



The SCS hardware is composed of the stimulus

microcomputer, an interface to the parallel link, and a 12 bit digital to analog converter. Its function, in conjunction with appropriate SCS software, is to generate analog waveforms that control the movement of the Visual stimulus.- In this particular study, the major task of the SCS is to receive raw position (timer) data from the DAS, process the data, and update the stimulus position, all as quickly as possible in order to minimize the response delay between the subject's movement and stimulus movement. In order to achieve this, the stimulus microcomputer, an Ohio Scientific Challenger 1P microcomputer similar to the position microcomputer, was made operational at 2 MHz by swapping in faster chips and rewiring the clock inputs. A

..







69

6522 VIA chip was installed to provide ports for the D/A converter and the parallel link. The fl/A converter, discussed in detail in section C in the Appendix, is based on a NS DAC121QLCD chip, and control signals are derived specifically to enable it to perform at maximum speed in

conjunction with the SCS program operating at a machine language level. In addition, the interrupt handler of the computer's operating system, which was necessary to receive the raw position data with greatest time efficiency, suffered from a design error which had to be corrected (see section D.1 in the Appendix).





2.2.2 SCS Geometric Analysis



One of the main functions of the SCS is to calculate the desired stimulus position based on the position and orientation of the subject's head and the selected -feedback gain of a trial. This calculation, performed by the SCS software (section 2.2.3), involves the use of ten equations that are discussed in this section.

The first four equations are used to calculate the X

and Y coordinates of Sp 1 and Sp 2 which define the position and orientation of the subject's head (see Figure 4 and discussion in section 2.1.2). These equations are of the form shown in equation (5), section 2.1.2, except that the units of the coordinate values are changed to "rads" in

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order to simplify the remaining equations. A rad is defined as a length equal to the radius of the cylindrical stimulus screen and, although designed to be 80 cm, has been empirically found to be 77 cm (see section 2.3.2). The generalized expression of these four equations for a coordinate value in rads is then

(6) CV = ((CA)2 (CB)2 + 351(CB CA))/12498510 where CA and CB are sp-mic pair raw position data that are picked by the SCS software based on its error checking and correcting functions. See Table 1, section 2.1.2.

The next four equations are used to calculate the

stimulus position for the normalized case of unity feedback gain. This case corresponds to the stimulus moving with the subject's head so that it appears stationary to the subject. Referring to Figure 4, section 2.1.2, the intent is to calculate the stimulus angle e such that the stimulus projection line (L3) intersects the subject's line of sight (a segment of line L2) at the surface of the screen. A subject standing at the center of the screen (on the axis of rotation) and facing straight ahead (along the Y axis in its positive direction) would result in e = 00. The equation of the line that includes the subject's line of sight (L2) is defined as

(7) x = mY + b

meaning that m = 0 corresponds to the subject facing straight ahead (parallel to the Y axis). Line L2 is assumed

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to be orthogonal to the line connecting the acoustic sources

(Li), and thus the slope of line L2 is

(8) m = (Y2 YI)/(X2 Xl)

Line L2 bisects line Li at a point whose (Y,X) coordinates are ((Y1 + Y2)/2, (Xl + X2)/2), so from equation (7) the X' intercept of line L2 is

(9) b = (Xl + X2 m(Yl + Y2))/2

The equation describing the screen is

(10) X2 + y2= 1

since the screen radius is defined as 1 rad. The X coordinate of the intersection of line L2 with the screen, from equations (7) and (10), is then

(11) XP = b + mYp = (i (yp)2)

Squaring both sides of equation (ii) and solving the resulting quadratic equation for Yp, the Y coordinate of the intersection of line L2 with the screen is

(12) Yp = (- bm (m2 b2 + 1) )/(m2 + 1)

There are two values for Yp corresponding to two possible intersections of line L2 with the screen. Since it is known that the subject's line of sight is always in the positive direction with regard to the Y axis, the greater value of Yp is the only one of interest. In addition, if the radical in equation (12) is defined as

(13) S = (m2 b2 + 1)

then equation (12) becomes

(14) Yp= (- bm + S)/(m2 + 1)

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The tangent of the normalized stimulus angle, with the use of equation (11), is

(15) tan en = Xp/Yp = (b + mYp)/Yp

and finally, using equation (14) in equation (15) and simplifying, the normalized stimulus angle is

(16) en = arctan ((b + mS)/(S bm))

The following two equations are involved with initial position correction and trial feedback gain. The stimulus angle is initialized to 0' at the beginning of a trial to allow for the greatest possible stimulus movement in either direction before reaching the physical limits of the SPS (resulting in nonlinear "clipping"). The initial position and orientation of the subject might not be in absolute accord with the initial stimulus angle, and so as to prevent an abrupt initial stimulus movement at the beginning of a trial, these initial positions of subject and apparatus are coupled by setting an initial position correction offset. This also compensates for any malposition of the acoustic sources on the subject's head (i.e., subject's line of sight not being exactly orthogonal to, or bisecting, the line connecting the acoustic sources). This offset is then used in calculating each new stimulus position update in order to maintain smooth stimulus motion during the remainder of the trial. Thus the relative movement between the subject and the stimulus is maintained, although the absolute position of the stimulus is not solely determined by the present subject position. This is of no consequence in this study

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where the stimulus is a vertical grid pattern covering the full field of vision of the subject. The equation for the initial position correction offset is

(17) C = 8i Gen

where ei is the initial stimulus position, and G is the trial feedback gain condition. This equation is only used once during each trial with the first valid value of en calculated by equation (16). Once the value of this offset is established, then the equation for the actual stimulus angle that is used throughout the remainder of the trial is

(18) Ea = Gen + C

This actual stimulus angle is the final result that

needs to be sent to the 12 bit D/A converter for controlling the SPS. Before the result can be used however, it needs to be modified for compatibility with the converter. For the sake of time efficiency, this preconditioning of the actual stimulus angle is incorporated into equations (17) and (18) as they are used in the SCS software (see section 2.2.3).





2.2.3 SCS Software



2.2.3.1 Background. The SCS software, developed for this study, is an online system which manages the utilization of the received raw position data to generate analog waveforms which are user specified functions of this data. This software, which is the heart of the SCS, is

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involved with (a) the generation of a random sequence of trial stimulus conditions, (b) the initialization of the mass storage device for cataloging these trials into stored data files, (c) the task of reception, error detection and possible correction of the raw position data sent by the DAS, (d) the calculation of the position and orientation of a subject from each complete raw data sample, (e) the calculation of the desired stimulus position based on the subject position and orientation result and the trial stimulus condition gain or (f) the calculation of the desired stimulus position based on a distribution simulating the jitter introduced by the DAS's experimental uncertainties and the trial stimulus condition gain, and

(g) the conversion of the desired stimulus position to an analog form by interfacing with and generating waveforms used for the control of a D/A converter.

The major concerns in the development of this software were speed and size. The stimulus microcomputer only has 8K of user available RAM to perform all the above functions. Speed is of the utmost importance since this determines how long it takes for the most recently determined position of the subject to be reflected in an updated position of the st imulus. In order to maximize the speed of the software, all the online functions during a trial are performed at a machine language level. In addition, a number of unorthodox practices are incorporated which, while aiding with speed and size, make the code difficult to follow and to modify.

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The more complex equations, used in the calculations of the subject position and orientation and desired stimulus position, are evaluated using BASIC floating point variables and the available operating system ROM routines, but all a ccessed from the machine language level. The number of BASIC variables used is minimized by their multiple usage to reduce allotted variable array space and access time; however, this makes -the software maintenance difficult. In addition, some numerical constants are represented by variables to improve access speed, and equations are arranged with regard for the speed of different algebraic operations, all in order to reduce computation time. The machine language portion of the software consists of six routines imbedded in a BASIC program which performs off line tasks and acts as a user interface. The complete program with allocated memory uses all but about 100 bytes of the available RAM. Therefore, the BASIC portion has virtually no documentation included together with the code. -An operational overview of the software is presented in the following sections, and the actual code with separate documentation and memory map of -the system is presented in section D in the Appendix.



2.2.3.2 Pretrial operation. Operation of the SCS software begins with the BASIC program, DSTIM.BAS, generating a random sequence of trial conditions. There are 14 different trial stimulus conditions corresponding to

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(a) positive and negative feedback plus baseline conditions for 4 different nonzero values of stimulus gain, and

(b) both an eyes opened and eyes closed condition for zero stimulus gain (stationary stimulus) The eyes opened zero gain condition is picked twice in the generation of 15 randomly sequenced trials. The entire 15 trial sequence is repeated in reverse order (counter-balanced) for a total of 30 trials per subject run. The sequence is selected with the computer's pseudo-random number generator and begins with the (N x 15) th random number where N is the subject number (1 to 33). At the user's command, -the subject's trial list is printed as hardcopy and then downloaded to the DPS, to organize the filing of the forthcoming raw position data. DSTIM.BAS then pokes (loads) memory with initial values for buffers, code for the machine language routines, and algebraic equations in BASIC's intermediate code or "tokenized" form. The interface for the parallel link is initialized to effect an interrupt of the SCS when -the DAS is ready to transmit data, to notify the DAS when it is ready to receive each byt e, and to latch each byte when the DAS indicates data ready. The D/A converter interface is initialized for sending data and for generating waveforms involved with the production of control signals for the D/A converter (see section C.l in the Appendix) Some status and error flags involved with the operation of the machine language routines are now cleared offline. The mic error criteria values for online checking of the raw position data

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(discussed later in this section) are entered from DSTIM.BAS and poked into machine language code in order to simplify access. Information sent to the D/A converter initially centers the visual stimulus on the screen, and some numerical constants are assigned to BASIC floating point variables. The test condition for the first trial is displayed on the monitor along with "STIMULUS ERRORS= 0" and a message stating how to enter a different trial. Every occurrence of a stimulus error updates both the associated counter and the displayed message. The option to enter a different trial can be invoked by pressing the key at any point of operation to stop the SCS software. Then, by performing a warm start ( key), hitting any key and , and entering the command "GOT0999", DSTIM.BAS allows the user to resume the program at any requested trial in the sequence.

After the monitor display is updated, the interrupt

capability of the stimulus microcomputer is enabled and the software begins online operation. If the trial is a feedback condition, then the trial gain is preconditioned by a numerical factor to achieve compatibility with the D/A converter (as discussed in section 2.2.3.3) as assigned to the variable G, and the machine language routine, ERROR.MLP, is entered. If the trial is a baseline condition, a DSTIM.BAS routine is entered which simulates the stimulus position jitter induced by the DAS (discussed in section

2.2.3.4).

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2.2.3.3 Feedback condition trial. An operational flowchart of the machine language routines is shown in Figure 6. It begins with ERROR.MLP being either (a) just entered from DSTIM.BAS, or (b) looped back to after processing the previous data. After performing some initialization tasks, this routine checks the data error flag for a data use error, which occurs when a new sample data from the DAS arrives before the new data buffer is free (an overflow). This error indicates that the DAS sampling rate is too fast for the SCS to keep up with, and results in

(a) the SCS returns control to DSTIM.BAS, (b) an error message is displayed, and (c) the SCS program ends. If no data use error occurred then ERROR.MLP checks the data-in flag for the arrival of, and if necessary waits for, the new position sample raw data transferred from the DAS.

The DAS transmits position data grouped by acoustic source, and each transmission generates an interrupt that switches control to the interrupt handler, DYNHAND." First, DYNHAND checks the data-in flag to check whether the new data buffer is free, and if it is not, the data error flag is set and the handler returns from the interrupt. If the buffer is free, DYNHAND stores the incoming data group in its appropriate location in the new data buffer and then returns from the interrupt. This buffer can contain a complete raw position data sample (all the data groups) and DYNHAND only sets the data-in flag when the buffer is full.

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.I


Enter from BASIC w/desired Gain


79
S Interrupt by
Position Computer (C2)) Dynhand
. .*
Previous N Set Data UseI
Data Used? Error Flag

V
Receive -New Data


(Return from Interrupt) -.- Loopfo -" : Loop foJ Sp-Mic
Datum












U







S Sel
Preferer




.
Var.MLP: Assign to BASIC Variables
I & Declare Data Used .

EqRun.MLP: Calculate Stimulus Position
Using ROM Routines & Gain


:. .:1 Error Counter I
"~~~~~~ ~~~ . .: . . .,. ; ' "
D/A.MLP: . Term.MLP
P osition in N Return to BASIC : S Bounds w/Error Message
Y
SUpdate D/A
% . . .o. . . .
Figure 6. SCS Software Flowchart: Online Operation for
Stimulus Feedback Trials. Raw positional data from the
DAS are error processed and used in the calculation of a
variable gain visual feedback signal.


-" y
N Data Use
: -Error?
Y


New Data N
Received?
Return to BASIC Y (w/Error Message)









Window Criteria? Error Flag



pdate Pair Datum



Y Another
Pair?
N
ect Pair Data using ces & Pair Error Flags

Dat a N S



Termination Return to


IN
i c me BASIC

ilncrement StimulusI

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Upon determining that a new data sample has been stored in the new data buffer, ERROR.MLP begins error checking. The geometric relationships between acoustic sources and microphone/detectors, as depicted in Figure 4 (section 2.1.2), are referred to here. Each of the sp-mic pair data in the new data buffer, corresponding to one of the eight distances D1 through D8, is checked for meeting three criteria (whose test values were entered via DSTIM.BAS). Two criteria are minimum and maximum allowable values for the datum, each associated with the operational limits for these distances (i.e., the limits of the measurement volume) The third criterion is a window test based on the fact that an acoustic source can only move a finite distance between successive samples.

One problem of a window test is in allowing the

collection of valid data to "get started" from an initial situation of no pair data (all initial datum values are $0000). Another problem is to "catch up" after one- or more datum errors of a particular sp-mic pair since by then the acoustic source might have moved away from a previous position not to return to that vicinity again. The solution is a window comparison of a sp-mic pair datum with the last datum of that same pair which had passed the minimum and maximum criterion tests (but not necessarily the window test) This is implemented by having an old data buffer, structured like the new data buffer, which stores the sp-mic pair data to be used in the next collected data sample's

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window criterion tests. Whenever a sp-mic pair datum in the new data buffer fails either the minimum or maximum criterion tests, an error flag for that pair is set and the datum presently in the old data buffer for that pair is left unchanged. However, if these two criterion tests are passed, but the window criterion test is not, the error flag for that sp-mic pair is still set but, as when all the tests are passed, the new pair datum overwrites the datum in the old data buffer.

ERROR.MLP performs its error correcting function by

evaluating the results of these criterion tests and deciding whether to, and with which sp-mic pair data, effect a stimulus position update. The sp-mic error flags permit judgements as to whether each of the four coordinate values (two for each acoustic source) can be calculated using

(a)the default, or if not, (b) the alternative coordinate determinants, or if neither then (c) the stimulus position is not updated. See Table 1 in section 2.1.2 for default and alternative coordinate determinants.

If all four acoustic source coordinate values cannot be calculated, a flag is set and control is passed to TERM.MLP. This routine determines why the stimulus position update could not be accomplished. The possible reasons are

(a) true datum errors, (b) every datum in the first sample of a trial always fails the window test, or (c) the termination code was sent by the DAS signifying the end of a trial. In the first case, the STIMULUS ERRORS counter is

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incremented, the data-in flag is cleared indicating that the new data buffer is free, and the program returns to ERROR.MLP to await the arrival of the next position data sample. The second case is treated similarly except that the STIMULUS ERRORS counter is not incremented. In the third case, further interrupts are disabled and the program returns to DSTIM.BAS which then reports the end of the trial and prepares for the next trial in the sequence.

If all four acoustic source coordinate values can be calculated then the sp-mic pair data are arranged in appropriate locations in the new data buffer, which now serves as an "equation variables buffer", to be assigned to BASIC variables by a routine called VAR.MLP. This buffer is reorganized in a manner which capitalizes on the existing positions of the pair data within it in order to minimize the amount of data movement and time expenditure necessary (as shown in section D.4 in the Appendix). In order to avoid any data loss due to overwriting in the equation variables buffer, any sp-mic pair data that needs to be moved is read from the old data buffer (which by now contains the pair data from the present sample) into this buffer.

VAR.MLP now assigns each of eight BASIC variables

(S through Z) to a different 2 byte datum in the 16 byte equation variables buffer, corresponding to the eight distances chosen to be used in the calculation of the acoustic sources' coordinates. This is accomplished by

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using (a) an operating system ROM routine which converts each 2 byte datum to a floating point number, (b) another ROM routine which creates BASIC floating point variables, and (c) a third ROM routine that sets pointers which equate the variables to the numbers. With all the BASIC variables assigned, the data-in flag is cleared to indicate that the equation variables (or new data) buffer is now free.

The process continues with a routine, EQRUN.MLP, directing calculations using the algebraic equations previously loaded into memory in BASIC "tokenized" form by DSTIM.BAS. A pointer is set to the location of each equation which is then evaluated by a ROM routine. The first four equations, used to calculate the four coordinate values, are in the form of equation (5) in section 2.1.2 and in BASIC nomenclature are

(19) S = (T*T-S*S+P*(S-T))/Q

(20) T = (V*V-U*U+P*(U-V))/Q

(21) U = (Y*Y-Z*Z+P*(Z-Y))/Q

(22) V = (X*X-W*W+P*(W-X))/Q

where the variables S through Z on the right sides of the equations were assigned by VAR.MLP as described above and the variables S, T, U, and V on the left sides of the equations correspond to the coordinates Y1, Xl, Y2, and X2 respectively. As previously described, the multiple use of BASIC variables saves memory and execution time, as does the multiplication of a variable by itself rather than squaring it, and also the use of the variables P and Q rather than

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numerical constants. DSTIM.BAS previously assigned the values P = 351 and Q = 12498510 offline, with Q being different than in equation (5) in order to have the units of the coordinates come out in rads (1 rad = 770 mm).

The next four equations, used in calculating the

normalized stimulus angle, are taken from equations (8),

(9), (13), and (16) in section 2.2.2 and in BASIC nomenclature are respectively

(23) W = (S-U)/(V-T)

(24) X (T+V-W*(S+U))/A

(25) Y = SQR(W*W-X*X+N)

(26) T = ATN((X+W*Y) /(Y-X*W))

Again, the definitions of variables might change in each equation, but they can be ascertained by comparing these equations with those they are taken from. The two variables, A and N, were equated to the numerical constants, 2 and 1 respectively, by DSTIM.BAS. The normalized stimulus angle, T, is expressed in units of radians by the arctan ROM routine, ATN.

The last two equations, used in calculating the initial position correction offset and actual stimulus angle, are taken from equations (17) and (18) in section 2.2.2 and in BASIC nomenclature are respectively

(27) C = C-G*T

(28) T = G*T+C

When EQRUN.MLP is entered for the first time in a given

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trial, equation (27) is used to calculate the initial position correction offset, C (on the left side of equation (27)), and the initialization flag is set so that this equation is bypassed in subsequent usage of this routine. The actual stimulus angle, T (on the left side o f equation (28)), is the result to be sent to the 12 bit D/A converter for controlling the SPS. Incorporated into the calculation of T is a preconditioning for compatibility with the D/A converter. The angle sent to the converter first needs to be converted to an integer in the range of 0 to 4095 (a 12 bit binary number) corresponding to a stimulus movement range of Q0 to 320 (as dictated by the limitations of the SPS as discussed in section 2.3.2) It should be noted that the preconditioning includes a change of convention for the stimulus angle from a straight ahead position (along the Y axis in Figure 4) being called 0' to being called 160. After the angle is converted to an integer, it needs to be left justified 4 bit positions so that its most significant bit is the most significant bit of a 2 byte word (as discussed in section C.1 in the Appendix). Two of these left shifts are later performed by a D/A converter handling routine, D/A.MLP, as part of its out of bounds error detecting function, and so only two left shifts are incorporated into this present calculation of T.

For any stimulus angle within the acceptable 160 160 range, the calculation of the preconditioned actual stimulus angle in equation (28) will result in the BASIC floating

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point variable, T, having a value between 0 and 16380 ($0000 and $3FFC). The routine D/A.MLP begins by using a ROM routine to convert the angle T to a 2's complement 16 bit integer. In this form, an angle within the acceptable range has its two most significant bits being Os since the preconditioning only included two of the four left shifts needed for full left justification of the original 12 bit number. This allows for quick testing of an angle to determine if it is within the bounds imposed by the SPS, which in turn is now reflected in the input capability of the D/A converter. D/A.MLP performs a left shift on the 16 bit integer, and if the overflow bit is a 1, then the angle is less than 0' (a negative value) and the stimulus update is aborted. If the angle is not less than 00, then another left shift is performed, and if the overflow bit is a 1, then the angle is greater than 320 (32' would now be represented by the value $FFFO) and the stimulus update is aborted. In the event of an abort which ends the trial, the error and clipping flags are set, further interrupts are disabled, and control returns to DSTIM.BAS. For the convenience of the user, DSTIM.BAS provides the option of either repeating the trial or going on to the next trial.

If the angle was within the acceptable range, then

D/A.MLP transfers the 16 bit number, a byte at a time along with the appropriate control signal generating bytes (see section C.I in the Appendix), to the D/A converter. A pause during the transfer, necessary because of the converter's

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operating and settling times, is efficiently used to perform some initialization for the forthcoming next operation of ERROR.MLP. Upon completion of the transfer, which results in the stimulus position update, the program returns to a postinitialization entry point in ERROR.MLP for processing the next position sample data in the trial.

Preconditioning for D/A conversion is accomplished by the utilization of numerical constants in the equation variables as follows. An angle expressed in radians can be converted to the proper form by multiplying it by the factor J where

J = 180/pi (degrees/radian) x 4096/32 (digital levels/degree)

x 4 (effects two left shifts of a binary number)

= 29335.439

In equation (28), the value of T on the left side would then be in the proper form if C (the initial position correction factor) already was in that form, and the term G*T was multiplied by J. This C (the initial position correction factor) would be in the proper form if in equation (27), C on the right side (the initial stimulus position) already was in that form, and the term G*T was multiplied by J. Since the stimulus is initially centered on the screen by DSTIM.BAS, the initial stimulus position, C, in the proper form, is 160 x pi/180 (radians/degree) x J = 8192. This numerical value for C is assigned by DSTIM.BAS before the beginning of the trial. The multiplication of the term G*T by J in both equations (27) and (28) is accomplished (as was

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mentioned in section 2.2.3.2) offline by DSTIM.BAS multiplying the trial gain G by the factor J just before ERROR.MLP is entered.



2.2.3.4 Baseline condition trial. For a baseline

condition trial, DSTIM.BAS uses a routine which simulates the stimulus position jitter induced by the DAS. This jitter is a result of noise and of fluctuations in the characteristics of the DAS components, and because of the quantizing effect of the DAS timers, it appears as a discrete variation in the stimulus position. A discussion of the design of the simulation, and a justification of its validity, appears in section D.6 in the Appendix. The routine begins by waiting for a complete raw position data sample to be received by the SCS (as indicated by the setting of the data-in flag which it-then clears), after which a time-out counter is cleared and a random number between 0 and 1000 is selected. This number is used to access a weighted tree which returns a normalized integer stimulus rotation angle from -7 to +7. These integers, when multiplied by 0.0434', yields stimulus position angles such as are observed with the jitter introduced when unity gain feedback is employed and a stationary headpiece is positioned at the center of the SPS. The preconditioned actual stimulus angle is calculated from

(29) Y = 32768+C(0,T)*Y*89

..


Full Text
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