evaluating manual control devices for those with tremor

VeteransAdministration

Journal of Rehabilitation Researchand Development Vol . 24 No . 2Pages 99—110

Evaluating manual control devicesfor those with tremor disability*

PATRICK O . RILEY AND MICHAEL J . ROSENMassachusetts Ins to of Technology, Cambridge, Massachusetts 02139

Abstract-Tremor disabled subjects were tested in twodimensional tracking tasks . The subjects had actiontremor due to various etiologies . Both continuous anddiscrete targets were used . Displacement sensing andforce sensing joysticks were compared. The effect offiltering of the control signal was evaluated . Position andvelocity control were compared . While individuals werefound to benefit from various combinations of controlsetups, no single control modification or combination ofmodifications was beneficial to all . It remains necessaryto adapt manual control interfaces to the needs of theindividual disabled person . Most customizing can beimplemented with software.

INTRODUCTION

From a clinical standpoint, the management ofabnormal involuntary movement is a worthwhiletarget for research because of the substantial num-bers of people involved, because of the potentialfor return of function, and because of the intracta-bility of many cases to conventional modes oftreatment . Abnormal involuntary movement is seenin cerebral palsy, multiple sclerosis, Parkinson'sdisease, Frledreich's ataxia, chronic alcoholism,cerebellar injury, monosymptomatic essential tremor,and other congenital, acquired, and degenerativeneurological conditions.

*This work has been supported in part by a grant from the NationalInstitute of Handicapped Research, Department of Education, Grant#6008300074 ; by the Eric P. and Evelyn E . Newman Laboratory forBiomechanics and Human Rehabilitation Fund ; and, by the Fred M.

Roddy Foundation .

The work described in this report is aimed spe-cifically at investigating the effects of joystick in-terface characteristics on control accuracy in thepresence of pathological "intention tremor ." Thisabnormality, commonly seen in people with lesionsof the cerebellum and basal ganglia, due, for ex-ample, to multiple sclerosis, may be defined as arhythmic oscillation of a limb induced or aggravatedby attempted voluntary movement . In severe cases,its amplitude may be comparable to purposeful acts,so that loss of independent function may be com-plete. The frequency of oscillation is dependent onthe limb segment studied, but frequencies in the 2to 6 Hz range are typical . Higher frequency phys-iological tremor (9–11 Hz) is seen in all individualsand has been observed by workers in this laboratoryto coexist with the lower frequency intention tremor(1) . In earlier work of the authors and their col-leagues (2,11) it was observed that intention tremorcontaminates voluntary activity in a simple additiveway, so that, for example, voluntary tracking of aperiodic target movement may be extracted frommovement records by ensemble averaging triggeredin synchrony with the target . Intention tremor maybe disabling in spite of functionally adequate strength.

HYPOTHESIS

As detailed below, this research is investigatingboth mechanical properties and signal processing

99

100

Journal of Rehabilitation Research and Development Vol . 24 No . 2 Spring 1987

aspects of control interfaces . The expectation thattremor may be modified by these means arises fromseveral sources . Adjustment of the spectral contentof normal control of limb position by manipulationof the visual display throw

which the task ispresented has been demo (16) . Normal phys-iological tremor has also been shown by numerousauthors (7,10,14,15) to be adjustable in amplitudeand frequency by application of inertial and elasticloads . While far less frequently reported, modulationof pathological tremor has also been observed bothclinically (5) and experimentally (3,9) . The presentauthors and colleagues have reported experimentsin which viscous damping was successful in pro-ducing selective reduction of intention tremor duringone degree-of-freedom tracking tasks (1,2,1 1).

The feasibility of mechanical modif ,.ion of tremoris also suggested by hypothetical tre

rgenic mech-anisms . Systems theory stig.4 'e models orcontributing phenomena . The Diomechanical reso-nance hypothesis (8) treats the muscle-limb plant asan underdamped sprin g mass system with tunedoscillations driven by

ad-band muscle force os-cillations . Closed n( „1scular loops, e .g ., spinalreflexes, are also capable of unstable oscillations(12,17), especially considering the presence of delayelements and pathologii-e ll -- 1;creased gain . Simplestof all, a central nervous s, tem

--dilator” may

drive the neuromuscular loops at . the observedtremor frequencies (4,6) . At this point, the work ofthe authors and colleagues suggests a dominant rolefor the third mechanism in the generation of intentiontremor (1).

Und r ( e h c 1' these hypotheses, mechanical load-ing is a rmicheal approach . Applied loads may beviewed either as a potential source of series com-pensation for loop oscillators or mechiinui al filteringgiven a central drive . Isometric rest

eoupledwith force sensing eliminates the lin ss termfrom the biomechanical plant, reducing the systemorder and hypothetically eliminating the possibilityof resonance.

METHODOLOGY

Test subjects w

required to performof visual targeting tasks in two dimensions.The tests were peiiormed using th— perimentalsetup shown in Figure 1 . The sm

was seatedfacing a 10 cm by 10 cm display of h the targetand cursor appeared (Figure 2) . The joystick wasrig"ly mounted in such a way that height and attitude

be adjusted . The weight of the subject'slot earm was supported by a feeding assist orthosiswhich permitted low friction movement in the hot. -

Setup : UM = Input, R(t) = Response, T(t) = Target

101

RILEY AND ROSEN, Manual control device for tremor disability

izontal plane and rotation in the vertical plane aboutthe forearm support point . This arrangement mini-mized subject fatigue and provided a degree of trial-to-trial uniformity in the way the joystick wasgrasped . The subject was otherwise unconstrained.

The microcomputer used, an ADAC system 2000,incorporates A/D and D/A capability . Two joystickswere used, a two axis force sensing joystick (Meas-urement Systems, Inc ., 435 DC) with a stiffness of0.0014 mm/newton and a displacement joystick(Measurement Systems, Inc ., 521T) modified byeliminating the return springs . An 8th order analogButterworth antialiasing filter with a 14 Hz cutoff(0.35 x sampling frequency) was employed . Thisfrequency permitted observance of higher frequency(9—11 Hz) tremor if present . The target signal, T(t),generated by software in real-time, was designed toappear to be random.

For each t of tracking task a number ofparameters wt used to evaluate subject perform-ance. The eon nuous target tracking error wasdefined as :

AHTR = 180 - HTR

where

.HS R = J Gs( ) do/ ,f GTT(0) &a

[2]

and GTR and GH are cross and auto power spectra,and the inte ails are evaluated over the frequencyband of t- ower (less than approximately 2Hz) . Thus —/R 11 a measure of the average trackingtransfer function . The tremor power was defined as :

Target-lower leftResponse-on center

GRR(w)(1

'YTR(W))

[3]

where ryTR - coherence of the target and response.

GRR the response auto power spectrum.

Here the integral was evaluated from 2 Hz to theantialiasing file

queney (—14 Hz) . The signal tonoise ratio et

' led as:

SNR

Gm(w)dw/PT[4]

where the into

was evaluated over the frequencyband of interc

ite denomh ) ntor is defined aboveand represents the power

ated with "noise,"w

The numerator is the power

b . On Target

Figure 2CRT Display

associated with the portion of the response linearlyrelated to the Dirge ,

A control effort

t r r as:

E

U 2 (t) dtl T 2(t) dt

[51

where 7(t) is the target signal measured in screenunits and U(t) is the joystick output voltage (seeFigure I)

Hidex provides a measure of the"cost" o

eved tracking performance in thepresence

interface and processing schemein terms of interface output signal power .

102


The condition of stationarity which must be metto employ the spectral averaging techniques usedto evaluate these performance parameters is metbecause the subject's response is made up of twocomponents, each of which is stationary under theconditions of these tests . Ideally, the target trackingcomponent follows the target closely . The targetwas designed to be stationary with a zero meanover the trail and over the briefer periods duringwhich individual FFT's were computed for aver-aging . The individual trials were designed to besufficiently brief so as not to exceed the subject'sattention span, assuring reasonably consistenttracking . Subjects whose data showed a trial-to-trialvariation of HTR indicating learning effects or de-creased attention were excluded from analysis . WhileStiles (13) has shown that the frequency and ampli-tude of normal hand tremor vary over periods onthe order of an hour, Adelstein (1) has shownintention tremor to be stationary over periods com-parable to the trial length.

For the discrete target tracking trials the param-eters measured were referred to as Settling Rate,Settling Time, Acquisition Rate, Response Time,and Error Power . Settling Rate (Rs) was defined asthe fraction of target position transitions for whichthe response came within and remained within + 20

percent of the transition magnitude of the target forat least the last 0 .5 seconds of the allotted period(approximately 6 .5 seconds) . Settling Time (Ts) is

the time from target transition to arrival of theresponse within the ± 20 percent band for thoseeases where "settling" occurred . Acquisition Rate(R A ) is the fraction of target transitions in which theresponse remained within ± 20 percent band for atleast 0 .5 seconds during the period . AcquisitionTime (Ts) is the time from target transition to thebeginning of acquisition . Error Power (Pr) wasdefined as the average of the square of the target toresponse distance from the beginning of the firstacquisition until the end of the period (time of thesubsequent target transition) . Figure 3 illustrates themeaning of acquisition, settling, and the associatedtimes . (Note that settling implies acquisition, butacquisition does not imply settling .) If the responseshown in Figure 3 had remained within the rangeafter acquisition, the acquisition and settling wouldhave occurred at the same time (TA = Ts).

The experimental design is represented in Figure4. This testing protocol permitted the direct com-parison of: 1) performance with filtering to perform-ance without filtering, 2) performance using velocitycontrol to performance using position control, and3) performance using a force sensing device to

Figure 3Settling (S) and Acquisition (A) Illustrated : TA = Acquisition Time, Ts = Settling Time

103


performance using a displacement device . Velocity.

.

.control implies that the response Cursor position 1Scontrolled by the time integral of the input signalU(t) ; position control implies that the responsecursor position is dirctly proportional to U(t) . Sincevelocity control is a form of filtering, the combinationwas considered redundant and not included.

The experimental protocol was the same for eachdevice and essentially the same with slight variationwith respect to total number of trials for all subjects.For each interface and control mode the subjectwas allowed to familiarize himself/herself with thesetup . The subject then practiced tracking for severalruns with each target type.

The subject then performed four to six tasks witheach target type and control alternative . Each tasklasted approximately 45 seconds, with 25 secondsof data taken from the middle of the record . Trialswere run at about two minute intervals.

Testing with a given interface lasted approxi-mately one hour . It was sometimes necessary toconduct the tests in more than one sitting to avoidsubject physical and/or mental fatigue . In these casesthe protocol was divided by interface device butwith some trials of each type with each interfaceperformed on each occasion to permit evaluation ofperformance stability.

Comparisons

Force

Displacement

Velocity

Position

Discrete

Continuous

Figure 4Experiment Design Tree

RESULTS

Six subjects were evaluated . Table 1 lists five ofthe subjects by initials and shows the etiology oftheir tremor. The subjects are ordered according todecreasing severity of tremor as measured by themean SNR for the reference condition (continuoustarget, unfiltered position control, displacementjoystick) . The tremor of the sixth subject, C .R.S.,was due to a midbrain stroke . This subject was notevaluated for continuous target tracking . Normalsachieved SNR's of greater than 20 for the referencecondition.

The tables which follow summarize the test re-sults . Three comparisons were made : 1) perform-ance with and without low-pass filtering of thejoystick output (Table 2) ; 2) performance using

Table 1Subject Information

Subject SNR Tremor Etiology

JAG 1 .314 Head InjuryRVM 1 .799 Multiple SclerosisRBT 7 .886 Head InjuryJBG 12 .774 Cerebellar AtaxiaEPS 13 .452 Cerebral Palsy

Interface

Control Mode

Signal Processing

Task

Utiltered

Level

104Journal of Rehabilitation Research and Development Vol . 24 No . 2 Spring 1987

velocity control versus performance using positioncontrol (Tables 3 and 4) ; and 3) performance usinga force sensing (isometric) joystick compared toperformance using a displacement sensing joystick(Tables 5 and 6) . Each result is given as a three-number cluster where the upper left hand numberindicates the number of subjects who achieved animprovement in the performance parameter in ques-tion (at a probability level p<0 .1) ; the upper righthand number indicates the number of subjects whoseperformance measured by the parameter deterio-rated (p<OA) ; and the lower number indicates thetotal number of subjects tested for the set of con-ditions in question . "Improved performance" meansthat the parameter in question changed in the desireddirection, i .e ., higher SNR, lower tremor power,shorter settling time, etc . The probability level p is

Table 2Filtering Effect Continuous Tracking, PositionControl

SNR

E

4 Hz filtering vs . unfiltered,

1/0

1/0force sensing

4


1/0

0/1force sensing

2


2/0displacement sensing


2/0

1/0displacement sensing

2

2

Table 3Velocity Control Effect Continuous Tracking,Unfiltered

based on unpaired t-tests of the difference of themeans of each parameter for all trials with the givenset of conditions.

The results of filtering for continuous target track-ing are summarized in Table 2 . These results areconsistent with the hypothesis that filtering canimprove SNR by reducing the tremor component ofthe control signal . While no negative effects areassociated with the 4 Hz filtering, degraded per-formance is seen with the lower cutoff frequency.An example of filtered and unfiltered tracking ispresented in Figure 5. The effect of filtering on thetremor power spectra is shown in Figure 6 . In thecase of discrete target tracking little likelihood ofachieving an improvement with filtering is demon-strated . However, there was a fairly consistentincrease, i .e ., degradation, of acquisition and settlingtimes when the 2 Hz filtering was used reflectingthe slower response of the filtered system.

When the velocity control was compared to un-filtered position control, the results, shown in Table3, indicate that, like filtering, velocity control alsoimproves SNR by attenuating the tremor componentof the input . Velocity control has a beneficial effecton SNR in a higher percentage of subjects with theforce sensing joystick than with the displacementjoystick. Velocity control frequently entails a pen-alty in tracking quality and control effort . Figure 7shows a comparison of tracking with velocity controland tracking with unfiltered position control.

Table 5Force vs . Displacement Sensing ContinuousTarget Tracking, Unfiltered

010

0/04

4111

0/22

20/0

1/05

0/02

0/0

2

SNR P 1177,

3/0 3/0 1/1Force Sensing 4 4 4

1/0 1/0 0/5Displacement Sensing 5 5 5

Table 4Velocity Control Effect Discrete Target Tracking,Unfiltered

I2A

Its

TA

1 E

3/0

1/0

0/1

1/05

5

5

5

0/0

0/0

0/1

0/16

6

6

6

5

SNR

1/2ete

I/I_et

0/4Position Control 4 4 4

1/0 2/0 1/1Velocity Control 4 4 4

Table 6Force vs . Displacement Sensing Discrete TargetTracking, Unfiltered

Rs

TATs

pF.

0/2

0/1

0/0

1/2

0/35

5

5

4

5

0/0

0/3

0/0

2/0

9/15

5

5

5

5

Position Control

Velocity Control

E

0/34

0/45

Force Sensing

Displacement

105


Table 4 presents the comparison of velocity con-trol with position control for discrete target tracking.Velocity control improved RA and Rs for somesubjects with force sensing but was never beneficialwhen used with the displacement device . TA and Tswere frequently longer with velocity control.

Tables 5 and 6 compare performance using theforce sensing joystick to performance using theposition sensing joystick . Control effort (E) is notpresented because force generating effort and dis-placement generating effort were not directly com-parable under the test conditions. Performance oftenimproves with the force sensing device, but degradedperformance is more common .

For the trials in which the effect of filtering wasbeing evaluated, the visual display presented to thesubject reflected the filtered version of the subject'sresponse. It was, therefore, possible that the subjectcontrolled the filtered response in a different waythan he/she controlled the unfiltered response, pro-ducing a result different from that which would bepredicted for application of the filter outside thevisual feedback loop . This question was addressedby a three-way comparison: performance with fil-tering present on-line (effect visible to the subject),performance without filtering, and performance withfiltering performed off-line (not fed back to thesubject) . Off-line filtering trials were generated by

Figure 5Filtered and Unfiltered Tracking : response, 0 target

1000 Filtered tracking

C .0

0

2 .0Time(sec)

106


0.050 Fi ered

0 .000_

0.004 Po -filtered

4,

3a.. 0 .000 0

.0Frequency (Hz)

5 .0

10 .0

15 .0

Figure 6Subject RVM, unfiltered, filtered, and post-filtered tremor power spectra

107


post-filtering the input, U(t), recorded during unfil-tered trials with digital filters matched to the filtersused on-line.

In general, performance with on-line filtering wasequal to performance with off-line filtering (p>0.9).In a few cases the subjects performed better withon-line filtering than would have been predicted byoff-line filtering . The performance of one subjectwith a 2 .5 Hz on-line filter was not as good aspredicted by off-line filtering.

The effect of varying the gain for position controlwith the force sensing device was tested with foursubjects . Previous work with isometric force sensingcontrol devices (1) had indicated that SNR improvedwith decreased gain, i .e ., as more voluntary torque

was required for a given display excursion . Thehypothesized mechanism for this effect was that theamplitude of force tremor remained essentially con-stant while the total force level increased, resultingin an increase in the signal (voluntary force) to noise(tremor force) ratio. This has been observed forisometric torque generation about a single joint, thewrist (1) . The purpose of this test was to see if asimilar overall efffect could be obtained in a lessconstrained, more functional control setup.

Table 7 presents the results of a linear regressionthrough the gain test data . In general, a negativecorrelation of SNR with gain was found, consistentwith the hypothesis that lower gain results in ahigher SNR . The minimum gain must, of course, be

Figure 7Position and velocity control tracking : e response, 0 target

l000 Velocity control

108


Table 7SNR vs. GAIN (Normalized) Force Sensing,Unfiltered Position Control

Subject Intercept SlopeSignificance

Level (P) F R I

JBG 1 .809 — .809 .218 1 .6 .09EPS 1 .302 — .302 .075 3 .95 .283RVM 1 .065 — .271 .014 19 .76 .523RBT .784 .216 .461 .5811 .0462

*F = Ratio (Between Mean Square)/(Within Mean Square) ; R 2 -=Fraction of Variability Explained, Correlation Coefficient Squared.

such that the subject is able to achieve full scaledeflection with a reasonable fraction of maximumvoluntary effort . For subject RNA ., whose SNRdecreased most significantly with increasing gain,both the tremor power and tracking error increasedwith gain . For this same subject a linear regressionof input tremor against gain also showed a positiveslope. This indicates that tremor, if it increases atall with increased effort, increases more slowly thantotal effort.

Besides the range of tremor etiologies and theexpected variance of individual performance, an-other factor which might have accounted for someof the variability in performance improvementachieved with the various techniques tested was thesubject-to-subject variation in the severity of tremor.Ranking the subjects by tremor severity, however,showed that neither the improvement nor the wors-ening of performance seemed to cluster at eitherend of the tremor severity spectrum . In other words,the likelihood of achieving an improvement in per-formance is not particularly related to the severityof the tremor . Since more severe tremor is moredisabling, any improvement achieved probably im-plies greater restoration of function.

DISCUSSION

The comparisons of filtered w ith unfiltered proc-essing, velocity with position con .nd force withdisplacement sensing do not den consistenteffects that would permit predicting that a giventechnique would benefit all users . However, it wasshown that each of the techniques can be beneficialto certain individuals . Variation among individuals,or perhaps among tremor etiologies, may ultimatelymake it necessary to assess each individual in order

to prescribe an appropriate interface and controlmode.

For example, the results for subject R .V .M . dis-played in Table 8 show that both 4 Hz filtering andvelocity control are effective in improving SNR.This subject also performed better with the forcesensing device than with displacement sensing . Thepoor results achieved with the 2 .5 Hz filter are ofinterest and will be discussed below . This subjectwould benefit from 4 Hz filtering if using a displace-ment sensing joystick and position control . He mightalso benefit from a force sensing device with velocitycontrol in situations where accuracy constraintswere not severe and fatigue was not an issue.

Filtering was expected to improve SNR by re-ducing the tremor component of the response signal(PT) without affecting the control error (AH IR )i Theresults indicate that where an improvement in SNRis achieved, there is in fact a decrease in P T . AHIRis not always unaffected, however ; both increasesand decreases in tracking error are seen . Filteringtremor from the displayed response may enhancethe subject's ability to detect tracking error, ex-plaining improvements in tracking . This would re-solve those cases where performance with on-linefiltering was superior to that predicted by off-linefiltering.

The decrements t -king fidelity, i .e., increasesin B.HIR, observed

some filtered D- i e s may be afunction of decreased system responWhilethe filtering employed did not sign

ttenuatethe response signal at frequencies

,ponding totarget power, ti eking of a random signal wouldcertainly be tated if system bandwidth weregreater than target bandwidth . The more frequentoccurrence of degraded tracking with the lowerfiltering cutoff frequency is consistent with thisinterpretation . Additionally, users may set lowerstandards for their performance if they considertheir device unresponsive . This may I

been truein the case of subject R .V .M ., whos

`brmancewith the 2 .5 Hz filter on-line was not

rind as off-line filtering predicted.

Where velocity control resulted in an improve-ment in SNR, this was accomplished by reducingthe P component of the response signal, Velocitycontrol also frequently resulted in incr trackingerror (AH1R ) and increased control coon (E) com-pared to unfiltered position control . Velocity controlwas generally more successful in conjunction withthe force sensing dey'

-

109


Table 8Subject RV— Continuous Tracking

Fixed Conditions

SNR

P

HTR

E

Force SensingPosition ControlDisplacement SensingPosition ControlForce SensingPosition ControlForce SensingUnfilteredDisplacement SensingUnfilteredPosition ControlUnfilteredVelocity ControlUnfiltered

*Not compared

Comparison Variable

4 Hz Filtering vs . Unfiltered

2 .5 Hz Filtering vs . Unfiltered

Velocity vs . Position Control

Force vs . Displacement Sensing

+

*

The best SNR for the combination of force sensingand position control is achieved when the gain inminimized within limits set by the subject's strength.While the question of fatigue was not quantitativelyaddressed during these tests, it seems likely thatthere would have to be a tradeoff between theimprovement in accuracy achieved and the increasedlevel of work required by the subjects.

CONCLUSIONS AND RECOMMENDATIONS

The study did not indicate that any of the systemfeatures evaluated could be expected to allow op-timal tracking performance for all tremor disabledpersons. It did, however, suggest that, on an indi-vidual case basis, a feature or combination of fea-tures can be found to exist which result in improvedtracking with respect to performance with the"standard interface," i .e ., displacement sensing andunfiltered control of position . Equally important isthe result that for each individual, some systemfeatures can result in seriously degraded perform-ance relative to the standard interface . This high-lights the need to evaluate clinically a broad range

of control A configurations to find the one bestsuited to the "vidual patient . All testing was donewith a single computer system and a very limitedamount of special hardware, demonstrating that itis possible to evaluate performance with systems ofvarying characteristics by evaluating them with asingle readily available and inexpensive assessment

tool . The importance of assistive devices which arethemselves programmable and thereby customizablewas also suggested.

Further study is needed in several areas . Controlvia isometric force sensing seemed to improve withdecreased system gain, but the effect of fatigue onperformance with a low gain system needs to beevaluated. The improved SNR with velocity controlseemed to be obtained at the expense of less accuratetracking for most subjects, but it would certainly beof interest to see if this could be corrected bypractice and skilled coaching . If so, the improvementin SNR seen with velocity control would be moresignificant.

This study has demonstrated that control accuracyof tremor disabled persons can be improved by theselection of suitable interface characteristics . Thetesting necessary to select the most favorable char-acteristics requires only a brief (about 1 hour)protocol which can be implemented in software onany laboratory computer, including the now stand-ard PC compatibles . This should provide clinicalengineers with a valuable tool in their efforts toassist persons with this severe disability.

Acknowledgments

The assistance of Dr . Mark Hallett and Dr . Jorge Romero inreviewing the test protocol and in identifying suitable subjectsis greatly appreciated . We are especially grateful to those whoparticipated as test subjects .

110


REFERENCES

1. ADELSTE.IN BD : Peripheral Mechanical Loading and theMechanism of Abnormal Intention Tremor . MS Thesis,Cambridge, MA : Department of Mechanical Engineering,M .I .T ., 1981.

2. ADELSTEIN BD, RosEN MJ: The Effect of MechanicalImpedance on Abnormal Intention Tremor . in: Proc 9thAnn Northeast Bioengin Conf, Piscataway, NJ : RutgersUniv ., 1981.

3. CHASE RA, CULLEN JD, SULLIVAN SA, OMMAYA AK:Modification of intention tremor in man . Nature, 483 :485–487, 1965.

4. ELBLE RJ, RANDALL JE: Motor unit activity responsiblefor 8- to 12-Hz component of human physiological fingertremor . J . Neurophysiol, 39 :370–383, 1976.

5. HEWER RL, COOPER R, MORGAN MH : An investigationinto the value of treating intention tremor by weightingthe affected limb . Brain, 95 :579–590, 1972.

6. JOFFROY AK, LAMARRE Y. Rhythmic unit firing in theprecentral cortex in relation with postural tremor in adeafferented limb . Brain Research, 27 :386–389, 1971.

7. JOYCE GC, RACK PMH: The effects of load and force ontremor at the normal human elbow joint . JPhysiol London,240 :375–396, 1974.

8. RIETZ RR, STILES RN: A viscoelastic-mass mechanism asa basis for normal postural tremor . J Appl Physiol, 37 :852–860, 1974.

9. RING ND, BROWN AWS, LORD M : An Investigation Intothe Control of Involuntary Movement . In : Future Priorities

in Orthotics and Prosthetics, London : Biologic

neering Society, 1980, p .57.10. ROBSON JG: The effect of loading upon the frequency of

muscle tremor . J Physiol London, 1.49 :29P–30P, 1959.11. ROSEN MJ, DUNFEE DE, ADELSTEIN BD : Suppression of

Abnormal Intention Tremor by Application of ViscousDamping . In : Proc 4th Fong Int Son Electrophys Kinesiol,Boston, MA: 1979, p . 4.STEIN RB, OGUZTORELI MN: Reflex involvement in thegeneration and control of tremor and clones . Prog ClinNeurophysiol, 5 :28–50, 1978STILES RN : Frequency and displacement amplitude rela-tionship for normal hand tremor . J Appl Physiol, 19 :357–360,1964.STILES RN: Mechanical and neural factors in posturalhand tremor of normal subjects . J Neurophysiol, 44 :40–59, 1980.STILES RN, RANDALL JE: Mechanical factors in humantremor frequency . J Appl Physiol, 23 :324—330, 1967.SUTTON GG, SYKES K: The effect of withdrawal of visualpresentation of errors upon the frequency spectrum oftremor in a manual task . J Physiol London, 190 :281—283,1967.WATANABE A, KIKUCHI H, FUTuMoTo I, SAITO M : Anal-ysis of micro-vibration frequency of human limbs duringstroke movement . In : Digest, 11th ha Con"' Med BiolEngr, Ottawa, Ontario : 1976.

12.

13.

14.

15.

16.

17 .

t

evaluating manual control devices for those with tremor

Documents