(Stroke. 1997;28:2162-2168.)
© 1997 American Heart Association, Inc.
Articles |
Computerized Measurement of Motor Performance After Stroke
From the Department of Neurology, Massachusetts General Hospital (S.C.C., G.N., J.D.K., S.P.F.); Spaulding Rehabilitation Hospital, Harvard Medical School (G.N., J.D.K.); Northeastern University, Bouvé College of Pharmacy and Health Sciences (J.D.S.); The Clinical Investigator Training Program, Harvard-MIT Division of Health Sciences and Technology and the Beth Israel–Deaconess Medical Center, in collaboration with Pfizer Inc (S.C.C.); and Massachusetts General Hospital/Spaulding NeuroRecovery Program (S.C.C., G.N., J.D.S., J.D.K., S.P.F.), Boston, Mass.
Correspondence to Steven C. Cramer, MD, VA Medical Center, Department of Neurology (127), 1660 S Columbian Way, Seattle, WA 98108. E-mail cramers{at}u.washington.edu
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Abstract |
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Background and Purpose Stroke scales usually convert motor status to a score along an ordinal scale and do not provide a permanent recording of motor performance. Computerized methods sensitive to small changes in neurological status may be of value for studying and measuring stroke recovery.
Methods We developed a computerized dynamometer and tested 23 stroke subjects and 12 elderly control subjects on three motor tasks: sustained squeezing, repetitive squeezing, and index finger tapping. For each subject, scores on the Fugl-Meyer and National Institutes of Health stroke scales were also obtained.
Results Sustained squeezing by the paretic hand of stroke
subjects was weaker (9.2 kg) than the unaffected hand (20.2 kg;
P<.0005), as well as control dominant (23.1 kg;
P<.0005) and nondominant (19.9 kg;
P<.005) hands. Paretic index finger tapping was slower
(2.5 Hz) than the unaffected hand (4.2 Hz; P<.01), as
well as control dominant (4.7 Hz; P<.0005) and
nondominant (4.9 Hz; P<.0005) hands. Many features of
dynamometer data correlated significantly with stroke subjects'
Fugl-Meyer scores, including sustained squeeze maximum force (
=.91)
and integral of force over 5 seconds (=.91); repetitive squeeze mean
force (=.92) and mean frequency (=.73); and index finger tap mean
frequency (=.83). Correlation of these motor parameters
with National Institutes of Health stroke scale score was weaker in all
cases, a consequence of the scoring of nonmotor deficits on this scale.
Dynamometer measurements showed excellent interrater
(r=.99) and intrarater (r=.97)
reliability.
Conclusions The degree of motor deficit quantitated with the dynamometer is strongly associated with the extent of neurological abnormality measured with the use of two standardized stroke scales. The computerized dynamometer rapidly measures motor function along a continuous, linear scale and produces a permanent recording of hand motor performance accessible for subsequent analyses.
Key Words: diagnosis • motor activity • stroke assessment
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Introduction |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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Hemiparesis constitutes the most common neurological abnormality after stroke, with a wide range in the severity of the motor deficit.1 A number of standardized scales have been devised to measure stroke deficits. These scales have widespread utility, including monitoring recovery, assessing therapeutic interventions, and prognostication.2 Each scale has its limitations, however.3–5 Some are insensitive to small deficits or require special skills to administer. The motor performance itself is not actually recorded but is instead converted to a discrete score along an ordinal scale. Most scales thus suffer from a lack of linearity.5
A device capable of rapidly measuring motor output along a linear scale may be of value in the evaluation of stroke recovery. The ability to subsequently review the performance or perform computational analyses would also be useful for obtaining a more detailed understanding of motor status after stroke. Therefore, we developed a computerized dynamometer to digitalize, store, and analyze motor performances. Previous studies of stroke patients have reported that maximum tapping frequency6,7 and squeezing strength7–9 are reduced in paretic hands compared with either unaffected hands or control hands. However, quantitative motor analysis has not previously been compared directly with other neurological assessments. The goals of the present study were to assess the extent to which dynamometer measurements of squeezing and finger tapping (1) distinguish the paretic hand of stroke subjects from the unaffected hand of stroke subjects and control hands and (2) correlate with scores on reliable10,11 neurological scales.
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Subjects and Methods |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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Dynamometer Construction
The main components of the dynamometer are a hand-held force transducer, an amplifier, an analog-to-digital converter, and a computer with strip chart–emulating software (Fig 1
). Two force transducers (SSM-AJ-50 and
SSM-AJ-250, Interface) were used: one with a 23-kg (50-lb) limit, used
for tapping studies, and one with a 114-kg (250-lb) limit, used for
squeezing studies. Each transducer was fitted with smooth, round,
plastic handles. Transducers were 9x8x3 cm, with a grip circumference
of 18 cm and a weight of 180 g. Each transducer converted
isometrically generated force into an electric signal. This signal was
carried to an amplifier (ETH-200, AD Instruments), then to an
analog-to-digital converter (MacLab, AD Instruments). The digital
output was fed into a Macintosh computer (PowerBook 540c or 5300cs,
Apple Computer) running strip chart–emulating software (Chart v.
3.5.1, AD Instruments).
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The computer, amplifier, and MacLab all plugged into a single extension outlet. This outlet was serially connected to an isolation transformer followed by a standard wall outlet, the transformer having been inserted to prevent electrical injury to test subjects. All of the apparatus was housed inside the shell of an electrocardiogram cart, allowing for transportation to the bedside.
Data Acquisition
Stroke subjects were identified over a 10-month period from the
admissions records of Massachusetts General Hospital and Spaulding
Rehabilitation Hospital, as well as from outpatient departments.
Elderly control subjects were recruited through local advertisements.
The entry criterion for control subjects was the absence of active
neurological disease. The entry criterion for stroke subjects was a
history of a stroke producing any hand weakness. Exclusion criteria,
defined by National Institutes of Health (NIH) stroke scale questions,
were decreased level of consciousness (any points on questions 1a, 1b,
or 1c), aphasia (
2 points on question 9), or neglect (2 points on
question 11). Approximately 1 in 3 stroke patients was eligible for
this study according to these criteria. Subjects provided informed
consent and then received dynamometer testing plus measurement of
scores on two reliable10,11 stroke scales. One was the NIH
stroke scale, a global scale designed to measure deficits in a number
of neurological domains. A form modified to be sensitive to distal
extremity weakness was used12; possible scores range from 0
(normal) to 44. The second scale was the Fugl-Meyer (FM) arm motor
subscore,13 a motor scale that assesses multiple features
of upper extremity motor function. Possible scores on this scale range
from 0 to 66 (normal). All dynamometer measurements and clinical scale
assessments were performed by two of the authors (S.C.C. and G.N.)
after being instructed by NIH and FM scale videos. Handedness was
evaluated with the use of the Edinburgh Inventory.14
Settings used for the strip chart–emulating software recording were acquisition of 40 to 100 data points per second, a low-pass filter of 50 Hz, and a high-pass filter of .05 Hz. Before each dynamometer use, the amplifier readout was set to zero with the transducers flat on a horizontal surface. The voltage output of the dynamometer was converted to kilograms by measuring the millivolt deflection occurring with suspension of two 100-g weights (McMaster-Carr) from the ends of the dynamometer. The linearity of the conversion was then confirmed by suspending two 2-kg weights. Subsequently, these weights were used to assess the fidelity of calibration every other week, with no deviation identified during the course of the study.
Dynamometer examination methods were based on previous recommendations.15 The subject was positioned either sitting or lying in bed with head elevated to 45°. Three tasks were performed with each hand: (1) sustained squeezing, (2) repetitive squeezing, and (3) index finger tapping. For squeezing, arms were placed onto a table with elbows flexed to 90° and wrists in neutral position. For tapping, the same position was used for the first 9 stroke subjects. Under these conditions, however, a variable number of upper extremity joints were used to tap. A support was constructed onto which the subject's forearm was secured by means of mid-ulna and mid-metacarpal hook and loop fastener straps. This restricted tapping movements to the index finger metacarpophalangeal joint and was used in subsequent subjects.
Squeezing was examined before tapping, and right hand was examined before left for each task. Subjects were given standard instructions to perform each of the following tasks until told to stop: (1) squeeze as hard as possible, (2) squeeze repetitively as fast and hard as possible, or (3) tap as rapidly as possible using only the index finger. Each subject was given an opportunity to practice, with feedback from the examiner when a task was performed improperly. Each task was then performed and measured for 7 to 10 seconds.
The examiner indicated the beginning and end of task performance verbally, simultaneously stamping these comments onto the recording using the Macintosh keyboard with a text feature of the strip chart–emulating software. Acquisition of dynamometer data for the three tasks required less than 6 minutes in most cases.
Analysis of Dynamometer Recordings
For tapping and repetitive squeezing, each recording was
converted to a series of cycles. Peak cycle values and time between
cycles were then exported to a statistics software program (JMP-In
3.1.5, SAS Institute). Measurements were made of mean force and mean
frequency for repetitive squeezing; mean frequency for index finger
tapping; and their respective coefficients of variation. For sustained
squeezing, the strip chart–emulating software was used to
directly measure parameters.
Statistical Analysis
Dynamometer values for stroke subjects' paretic hand motor
performances were compared with unaffected hand
performances as well as both hands of control subjects with the
use of Student's t test. No correction was made for
multiple comparisons. Two representative motor
parameters were evaluated: the maximum force during
sustained squeeze and the mean frequency during index finger tap.
Analysis of results on index finger tapping was restricted to
the 14 stroke subjects examined while using the arm support. A
normalized value was also compared between stroke and control subjects.
This normalized value was generated to account for intersubject
variability in squeezing and tapping.16,17 For control
subjects, the normalized value was nondominant/dominant hand
dynamometer values. For stroke subjects, the normalized value was
paretic/unaffected hand dynamometer values.
For stroke subjects, linear correlation analyses were done to
assess the degree of correlation of each dynamometer measurement with
(1) the score on the FM scale and (2) the score on the NIH stroke
scale. The Spearman rank-order correlation statistic, , was
used.
This study was approved by the Massachusetts General Hospital and the Spaulding Rehabilitation Hospital Human Studies Committees. The dynamometer was approved by the Massachusetts General Hospital Bioengineering Department.
Reliability Studies
Intrarater and interrater reliability were assessed in a
separate group of 10 right-handed subjects (5 control subjects and 5
stroke subjects), each of whom met entry criteria. Three independent
dynamometer studies were obtained on each subject during a 30- to
60-minute period: examiner 1 (S.C.C.) measured sustained squeezing and
index finger tapping by the paretic hand (stroke subjects) or dominant
hand (control subjects). These measurements were repeated by examiner 2
(J.D.S.). A final set of measurements was then obtained by examiner 1.
Both examiners subsequently measured the maximum force during sustained
squeezing and the mean frequency during index finger tapping from all
three data sets. Reliability was assessed with the Pearson product
moment correlation coefficient.
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Results |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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Dynamometer measurements and scores from neurological scales were obtained in 23 stroke subjects and 12 control subjects. The mean age of stroke subjects (66 years; range, 36 to 89 years) and control subjects (67 years; range, 61 to 76 years) was not significantly different (P>.5). All control subjects had normal NIH (0) and FM (66) scores. For stroke subjects, mean score on the FM scale (45) was significantly lower (P<.0005) and on the NIH scale (4) significantly higher (P<.0001) than that of control subjects. All control and 22 of 23 stroke subjects (premorbid status) were strongly right-handed; one stroke subject was ambidextrous and was treated as right-handed during analysis. There was a trend toward more men in the stroke group (18 of 23 male for stroke subjects, 5 of 12 male for control subjects; P=.059 by Fisher's exact test).
The median time after stroke was 22 days (range, 1 to 360 days). The location of the stroke was right hemisphere in 7, left hemisphere in 10, and infratentorial in 6 cases. The paretic hand was the right in 14 cases and left in 9. The index stroke was the first cerebral infarct in 19 of 23 subjects and the first symptomatic infarct in 21 of 23. Stroke mechanism was atheroembolic in 8 cases, small vessel in 14 cases, and hemorrhagic in 1 case. All subjects were able to generate a measurable performance for each task, except for 4 subjects who could not tap the paretic index finger; the mean FM score for these 4 subjects was 27 of 66.
Comparison of Stroke Subjects and Control Subjects
Examples of dynamometer recordings for sustained squeezing
and index finger tapping are shown in Fig 2. Values for paretic hand were
significantly lower than values for unaffected hand, control dominant
hand, and control nondominant hand during both sustained squeezing
maximum force (Fig 3A) and index finger
tapping mean frequency (Fig 3B). This remained true when the side of
paresis was considered during comparison with control subjects:
dynamometer values for subjects with dominant hand paresis were less
than control dominant hand values, and values for subjects with
nondominant hand paresis were less than control nondominant hand
values. The normalized values were significantly different between
stroke (paretic/unaffected) and control (nondominant/dominant) subjects
for both squeezing (0.50 versus 0.85; P<.005) and tapping
(0.62 versus 1.04; P<.005). No significant differences were
found between the unaffected hand of stroke subjects and either hand of
control subjects.
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Correlation of Dynamometer Values With Scores on Neurological
Scales
The Table shows the results of
correlating normalized values for motor parameters with
scores on FM and NIH stroke scales. In all cases, use of the normalized
parameter showed improved correlation compared with use of
the paretic hand value alone. This is demonstrated by comparing the
first two rows of the Table for the correlation between FM score and
sustained squeeze maximum force: the correlation using the ratio of
paretic to unaffected hand (=.91) is stronger than the correlation
using the paretic hand (=.81). None of the coefficient of variation
values, reflecting inconsistent motor effort, showed
significant correlation with scores on either neurological scale. Eight
of the 12 examined motor parameters showed significant
correlation with the FM arm motor score. For six of these
parameters, correlation with the NIH score was also
significant, although at a lower level than with the FM score. Linear
regressions for sustained squeeze maximum force and index finger tap
mean frequency are shown in Fig 4.
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Reliability
A high degree of intrarater reliability was found on comparing the
two sets of squeezing and tapping results obtained by examiner 1
(r=.97, P<.0001). The means were 18.77 kg versus
18.01 kg for maximum squeezing force and 4.01 Hz versus 4.33 Hz for
tapping frequency. Comparing squeezing and tapping results between
examiners 1 and 2 identified excellent interrater reliability
(r=.99, P<.0001); the means for examiner 2 were
16.67 kg for squeezing and 4.09 Hz for tapping. Both examiners
subsequently extracted dynamometer parameters from all
three sets of data; excellent interrater reliability for the data
analysis methods was found (r=.99,
P<.0001).
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Discussion |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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Two lines of evidence suggest that dynamometer measurements are a valid assessment of motor status after stroke. First, dynamometer measurements of paretic hand squeezing and tapping were lower than those obtained from the unaffected hand of stroke subjects, the dominant hand of control subjects, or the nondominant hand of control subjects (Fig 3
). This finding is consistent with previous
reports.6–9 Second, dynamometer-derived measures of motor
status correlate closely with scores on two standardized stroke scales,
the FM and NIH stroke scales (Table, Fig 4). This relationship has not
previously been described. Desrosiers et al18 examined grip
strength in the unaffected hand and found no significant correlation
with paretic arm FM score; correlation of affected hand strength with
FM score was not presented. For the measurement of motor status, use of this newly developed dynamometer offers several theoretical advantages over standardized clinical scales because of its use of a continuous, high-resolution, linear scale. First, although values from clinical scales are often treated as continuous variables in statistical testing,1 they are actually the sum of several ordinal variables, a comparatively weaker form of measurement.19 Second, direct measurement of squeezing and tapping produces data of higher resolution than most clinical scales. For example, three stroke subjects had an NIH score of 3. However, these three were not equivalent when tested with the dynamometer, with a range for index finger tapping frequency of 1.5 to 5.6 Hz and a range for sustained squeeze maximum force of 14.7 to 27.7 kg. The higher resolution of dynamometer testing may allow for improved ability to detect smaller changes in motor recovery over shorter time intervals. Third, there are fewer assumptions about data points in a linear scale. For example, improvement in squeezing from 20 to 30 kg represents a 50% increase in strength. A change in FM score from 20 to 30 corresponds to an undefined degree of neurological improvement.5 This advantage of a linear measurement will be valuable in future studies of stroke recovery employing serial dynamometer measurements; in this regard, the excellent intrarater and interrater reliability demonstrated for the dynamometer will also be important. Finally, a linear scale may better represent changes in motor cortex function after stroke, since the discharge rate of many cortical neurons has been shown to be linearly related to upper extremity force generation.20,21
Computational analysis of the digitalized dynamometer
recordings may also permit a more detailed understanding of
motor behavior than is available with the use of either standardized
clinical measures or a mechanical dynamometer. This is because motor
performances are recorded, permitting subsequent review and
analysis. As an example, measurement of multiple
parameters for squeezing (Table) provides a broader picture
of motor dysfunction than measurement of maximum force alone, the usual
output of a noncomputerized dynamometer. The correlation of maximum
force with stroke scale scores remained significant (Table) whether we
compared a sustained or a repetitively produced squeeze. The maximum
force and the integral of force over time were affected to a similar
extent after stroke. The decrement in motor output over 5 seconds (line
4 of the Table) showed significant correlation with the FM score. The
time to reach maximum force (Table, line 5) was used to test the
hypothesis that a weaker subject reaches maximum force more slowly, but
this variable did not show a significant relationship with FM
score. Overall, subjects with a greater motor deficit show squeezing
that is weaker but not slower in its onset. If the squeeze is
sustained, there will be a greater decrement of force and a smaller
integral of force over time. If a repetitive volley of squeezes
follows, these will be produced more slowly.
A number of variables complicate direct comparison of the current
data with prior reports. Differences in the instrument used for
measurement can influence motor findings.22,23 Previous
studies have assessed nonisometric forces because they employed a
mechanical dynamometer7–9,17 for squeezing and either a
key press6 or tally counter7,17 for tapping.
The current device measures squeezing and tapping isometrically. A
large number of variables can influence motor performance
after stroke, including side of paresis, time after stroke, lesion
volume, and stroke subtype.18,24,25 Despite these
variables, results of the current study were similar to prior
studies. For example, Colebatch and Gandevia8 studied 10
subjects, most of whom had cerebral infarcts. Mean grip strength was
9.3 kg in the paretic hand and 27 kg in the unaffected hand, with a
normalized ratio of 0.34. This is similar to the values found in the
present study (Fig 3A): 9.2 kg in the paretic hand, 20.2 in the
unaffected hand, with a normalized ratio of 0.46. Shimoyama et
al6 studied the paretic hand of 14 subjects with cerebral
lesions, 12 with strokes and 2 with tumors. They found that the mean
frequency for key tapping averaged 3.5 Hz for paretic index fingers,
similar to the 2.5 Hz value found with our dynamometer (Fig 3B). Values
for control subjects determined with the use of the present device
also compare favorably with measurements made in other studies.
Dominant hand index finger tapping by normal subjects in their seventh
decade averages 3.6 Hz with a tally counter17 compared with
4.7 Hz in the present control group. The difference in tapping
frequency may be due to the larger minimum force needed to produce a
tap with the mechanical tally counter. The normalized value with the
tally counter (0.95) is similar to the value (1.04) found in the
present study. Dominant hand squeezing by normal subjects in their
seventh decade averages 33.4 kg17 compared with 23.1 kg in
the present control group. This difference may in part be
attributable to use of a single grip size in the present study,
since breadth of grip can influence force exerted.26
Despite these differences, the normalized value with a mechanical
dynamometer (0.92) is similar to the value obtained in the present
study (0.85).
When the motor performance of the unaffected hand was taken into consideration, the correlation of paretic hand dynamometer values with neurological scales improved. This improvement reflects a correction for the normal variability in motor performance seen among subjects.16,17,23 Prior reports of a small motor deficit in the unaffected hand after stroke8,18 suggest that use of the normalized value (paretic/unaffected hand) for dynamometer parameters in stroke subjects may slightly overestimate motor deficits. However, deficits in the unaffected hand after stroke may be least pronounced in tasks with little sensorimotor interaction,9 such as squeezing. Thus, although one prior study identified a deficit in squeezing force by the unaffected hand,8 three did not.7,9,18 Haaland,7 examining 43 patients with unilateral stroke, did not find a difference in index finger tapping frequency between the unaffected hand and control subjects. Indeed, in the present study no significant differences in tapping frequency or squeezing force were found between the unaffected hand and either control hand.
Dynamometer measurements of arm motor activities showed stronger correlations with the FM arm motor score than with the NIH stroke scale score. This pattern was expected, given the nature of each scale. The FM scale evaluates multiple motor functions, all involving the upper extremity. The NIH scale, however, includes points for abnormalities in a wide range of neurological modalities, including motor, sensory, language, vision, articulation, and attention. In addition, the NIH scale scores motor deficits in the lower extremities. The improved correlation and significance with use of the FM scale compared with the NIH stroke scale implies that abnormalities detected by the dynamometer are primarily arm motor deficits.
Dynamometer measurements of tapping and squeezing are linear measures that correlated closely with scores derived from valid, reliable scales. The findings suggest that in alert, cooperative stroke patients, the dynamometer is a reliable instrument for accurate assessment of arm motor status. The dynamometer allows for rapid assessment of simple and higher order motor parameters. This may be of value in studying and in measuring small changes in motor status during the period of stroke recovery. Future studies will clarify the value of serial dynamometer measurements during the stroke recovery process and evaluate the correlation of dynamometer measurements with scales in other neurological conditions.
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Acknowledgments |
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This study was supported by a grant from the National Stroke Association (Dr Cramer). We are grateful to Pam Duncan, PhD, PT, for providing the training tape for the Fugl-Meyer scale. After completion of this study, a patent was filed on the described device by Drs Cramer and Finklestein. Thermocorps, Inc (Greenwood Village, Colo) has purchased the option to license the patent from Massachusetts General Hospital.
Received May 9, 1997; revision received August 28, 1997; accepted August 28, 1997.
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J. Cauraugh, K. Light, S. Kim, M. Thigpen, and A. Behrman Chronic Motor Dysfunction After Stroke : Recovering Wrist and Finger Extension by Electromyography-Triggered Neuromuscular Stimulation Stroke, June 1, 2000; 31(6): 1360 - 1364. [Abstract] [Full Text] [PDF]
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G. Nelles, S. C. Cramer, J. D. Schaechter, J. D. Kaplan, and S. P. Finklestein Quantitative Assessment of Mirror Movements After Stroke Stroke, June 1, 1998; 29(6): 1182 - 1187. [Abstract] [Full Text] [PDF]
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