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doi: 10.2522/ptj.20060135

Originally published online April 18, 20072007; 87:751-765.PHYS THER.

DromerickSahrmann, Dorothy F Edwards and Alexander WJoanne M Wagner, Catherine E Lang, Shirley ARecoveryHemiparesis During the First Few Months ofPerformance in Subjects With PoststrokeSensorimotor Impairments and Reaching

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Sensorimotor Impairments and

Reaching Performance in SubjectsWith Poststroke Hemiparesis Duringthe First Few Months of RecoveryJoanne M Wagner, Catherine E Lang, Shirley A Sahrmann, Dorothy F Edwards,Alexander W Dromerick

Background and PurposeLittle is known about the relationship between upper-extremity (UE) sensorimotor

impairment and reaching performance during the first few months after stroke. Thepurpose of this study was to examine: (1) how measures of UE sensorimotorimpairment are related to the speed, accuracy, and efficiency of reaching in subjects

with hemiparesis during the subacute phase after stroke and (2) how impairmentsmeasured during the acute phase after stroke may predict the variance in reachingperformance a few months later.

Subjects and MethodsUpper-extremity sensorimotor impairments and reaching performance were evalu-

ated in 39 subjects with hemiparesis at 2 time points: during the acute phase(8.73.6 [XSD] days) and the subacute phase (108.716.5 days) after stroke. Tensubjects who were healthy (control subjects) were evaluated once. Regression

analyses were used to determine which impairments were the best predictors ofvariance in reaching performance in the subacute phase after stroke.

ResultsOnly a small amount of variance (30%) in reaching performance was explained atthe subacute time point, using either acute or subacute impairments as predictor

variables. Of the impairments measured, UE strength deficits were the strongest, mostconsistent predictors of the variance in reaching performance during the first 3months after stroke.

Discussion and ConclusionSurprisingly, the detailed clinical assessment of UE sensorimotor impairment, mea-

sured at the acute or subacute phase after stroke, did not explain much of thevariance in reaching performance during the subacute phase after stroke. The find-ings that UE strength deficits (ie, decreased active range of motion and isometricforce production) were the most common predictors of the variance in reachingperformance during the first 3 months after stroke are consistent with the current

viewpoint that impaired volitional muscle activation, clinically apparent as UE weak-ness, is a prominent contributing factor to UE dysfunction after stroke.

JM Wagner, PT, PhD, ATC, is adoctoral candidate, Program inPhysical Therapy, WashingtonUniversity School of Medicine, St

Louis, Mo.CE Lang, PT, PhD, is Assistant Pro-fessor, Program in Physical Ther-apy, Program in OccupationalTherapy, and Department of Neu-rology, Washington UniversitySchool of Medicine, Campus Box8502, 4444 Forest Park Pkwy, StLouis, MO 63108 (USA). Addressall correspondence to Dr Lang at:[email protected].

SA Sahrmann, PT, PhD, FAPTA, isProfessor of Physical Therapy/Neurology/Cell Biology & Physiol-

ogy, Program in Physical Therapy,Washington University School ofMedicine.

DF Edwards, PhD, is Associate Pro-fessor, Program in OccupationalTherapy and Department of Neu-rology, Washington UniversitySchool of Medicine.

AW Dromerick, MD, is AssociateProfessor, Department of Neurol-ogy, Program in OccupationalTherapy, and Program in PhysicalTherapy, Washington UniversitySchool of Medicine.

[Wagner JM, Lang CE, SahrmannSA, et al. Sensorimotor impair-ments and reaching performancein subjects with poststroke hemi-paresis during the first few monthsof recovery. Phys Ther. 2007;87:751765.]

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Previous studies have investi-gated relationships betweenupper-extremity (UE) sensori-

motor impairments and motor func-tion or disability early after stroke,15

as well as the predictive value ofearly sensorimotor impairments indetermining later functional limita-tion and disability.613 These studiesused clinical rating scales that can beadministered at bedside. Althoughthese scales provide some informa-

tion about motor function, they donot provide specific informationabout the qualitative features of UEmovement (eg, accuracy).

Over the past decade, kinematic

studies in people with chronic hemi-paresis have yielded significant infor-mation about how movement con-

trol is altered after stroke andprovided insight into compensatorymovement control strategies (eg, seeCirstea and Levin14). Compared withclinical rating scales, kinematic stud-ies offer a sensitive, quantitativeassessment of the components ofabnormal motor performance (ie, de-creased efficiency and speed, poor

accuracy, impaired interjoint coordi-nation). Information from this typeof assessment could be beneficial ininvestigating relationships betweensensorimotor impairments and mo-tor performance, as well as the pre-dictive value of sensorimotor impair-ments in determining later motorperformance. A better understand-

ing of these issues in the acute andsubacute phases after stroke wouldhelp clinicians in designing and im-plementing UE rehabilitation proto-cols, especially because this isthe time when the majority of re-covery occurs15 and the time whenindividuals with stroke receiverehabilitation.16,17

We recently examined the relation-ships between sensorimotor impair-ments and the kinematics of reach-ing performance in a group ofsubjects with hemiparesis during the

acute phase after stroke.18We foundthat sensorimotor impairments ex-plained a moderate amount of vari-

ance in reaching performance andthat measurements of UE strength

(force-generating capacity) pre-dicted the largest proportion of vari-ance in reaching performance at thisearly time point after stroke (averageof 9 days poststroke). In the currentstudy, we extended our investigationto look at how sensorimotor impair-

ments relate to reaching perfor-mance in the subacute phase afterstroke and to look at how sensori-motor impairments measured in theacute phase after stroke relate toreaching performance measured

several months later.

We chose to study forward reaching

as a representative movement taskbecause: (1) reaching is a fundamen-tal component of many activities ofdaily living, (2) reaching requires thecoordinated movement of multipleUE segments, and (3) reaching hasbeen extensively studied in adults

who are healthy and in people withchronic hemiparesis to better under-

stand UE motor control.14,1928

Ofthe many variables that can be usedto quantify reaching performanceusing kinematic techniques (eg, seeTab. 2 in Cirstea and Levin14), wechose to quantify the speed, accu-racy, and efficiency of the reach. Weconsidered these 3 movement char-acteristics to be important because,

presumably, once in the communitysetting, patients will not use theirarm if movements are not timely oraccurate, or if it takes too much ef-fort or too many attempts to performthe movement. We hypothesizedthat reaching performance andsensorimotor deficits would recoverfrom the acute phase to subacute

phase and that strength deficitswould be the largest and most con-sistent predictor of variance in reach-ing performance during the first fewmonths after stroke.

MethodSubjectsThirty-nine subjects with hemipare-

sis resulting from stroke participatedin this study. Subjects with hemi-

paresis were recruited from theacute stroke service of Barnes-JewishHospital and the stroke rehabilitationservice of the Rehabilitation Instituteof St Louis, St Louis, Mo.

Subjects were included if they had:

(1) an ischemic or hemorrhagicstroke within 28 days of admissionfor inpatient rehabilitation; (2) per-sistent hemiparesis, as indicated by ascore of 1 to 3 onthe motorarm itemof the National Institutes of Health

Stroke Scale (NIHSS); (3) the pres-ence of some UE voluntary activity,as indicated by the ability to move

proximal or distal joints against grav-ity; (4) evidence of preserved cogni-tive function, as indicated by a scoreof 0 or 1 on the consciousness andcommunication items of the NIHSS,the ability to follow 2-step com-mands, as determined by clinicalstaff, and a score of 8 or lower on theShort Blessed Memory Orientation

and Concentration Scale29

; and(5) no injury or condition that lim-ited use of the UEs prior to thestroke.

Subjects were excluded if they:(1) could not give informed consent,(2) had clinically significant fluctua-tions in mental status in the 72 hours

prior to enrollment, (3) had hemis-patial neglect, or (4) were not ex-pected to survive 1 year due to otherillnesses (eg, malignancy). Character-istics and descriptive lesion informa-tion of the subjects with hemiparesisare provided in Table 1. Descriptivestatistics on performance on the Ac-tion Research Arm Test (ARAT)

(Tab. 1) indicated that, on average,the affected UE was moderately af-fected at the acute time point andmildly to moderately affected by thesubacute time point. The ARAT as-sesses UE activity limitation in peo-

Sensorimotor Impairments and Reaching Performance in Poststroke Hemiparesis

752 f Physical Therapy Volume 87 Number 6 June 2007


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ple with hemiparesis after stroke,30

and ARAT scores are strongly corre-lated with scores on the UE scale of

the Fugl-Meyer test (r.91.94).31,32

ProcedureThe sample of subjects with hemi-paresis in this study is the first groupof subjects participating in VECTORS(Very Early Constraint-induced Ther-apy for Recovery of Stroke), a single-center, randomized controlled trial

investigating early motor recovery ofthe UE following stroke conductedat Washington University School ofMedicine. As part of the VECTORSclinical trial, all subjects participatedin a 2-week (10 sessions) UE trainingprogram during inpatient rehab-ilitation.

Subjects were randomly assigned to1 of 3 treatment groups: (1) subjects

who received 2 hours daily of occu-

pational therapy, including compen-satory techniques for activities ofdaily living, UE strength, and rangeof motion and traditional position-ing (control group); (2) subjects whoreceived dose-matched constraint-induced movement therapy (CIMT)(2 hours per day of CIMT-based oc-cupational therapy, with 6 hours per

day of constraint); or (3) subjectswho received high-intensity CIMT(3 hours per day of CIMT-based oc-cupational therapy, with 90% wak-ing hours constraint). Subjects inthe control group also participatedin a circuit-training program allow-ing them to perform bilateral self-range-of-motion and functional activ-

ities in a supervised setting. Subjectsin the dose-matched and high-intensity CIMT groups received a

CIMT-based occupational therapyintervention that directed their at-tention and effort toward the hemi-paretic UE and minimized the use ofthe uninvolved UE during functionalactivities. Subjects in those 2 groupsalso participated in a circuit-trainingprogram encouraging the use of thehemiparetic arm with a variety of UE

and functional tasks. To discourageuse of the unaffected hand outside oftherapy sessions, subjects in thedose-matched and high-intensityCIMT groups wore a padded mitten(eg, constraint) on their uninvolvedUE during the 2-week treatmentperiod. The duration of occupa-tional therapy and mitten use var-

Table 1.Characteristics of Subjects With Hemiparesisa

Variable Acute Hemiparesis Subacute Hemiparesis

Age (y) 63.911.5 (3987)

Time since lesion (d) 8.73.6 (421) 108.716.5 (86171)

Sex 24 female, 15 male

Side of lesion 21 right, 18 left

ARATb 22.916.6 (057) 43.116.1 (057)

FIM-Motorc 58.411.7 (3678) 81.311.7 (4391)

Subjects with acute clinical imaging datad 85% (33/39)

Subjects with image data with identifiable

acute lesionse67% (22/33)

Type of stroke in subjects with clinical

imaging datae25 ischemic, 8 hemorrhagic

Lesion size in subjects with identifiable

lesions

f,g

1.5 cm7

1.63.0 cm

113.0 cm5

Uncategorized2

Lesion location in subjects with identifiable

lesions f28% (7/25) brain stem/cerebellum

24% (6/25) hemispheric, superficial

44% (11/25) hemispheric, deep subcortical

(white or gray matter structures)

4% (1/25) uncategorized

aValues represent group means SD (range) where appropriate.b ARATAction Research Arm Test, normal performancemaximum score of 57.c FIM-MotorFunctional Independence Measure, Motor subscale; normal performancemaximum score of 91 (13 scored items).d Lesion data from clinical magnetic resonance imaging or computed tomography scans obtained during inpatient hospitalization.e Computed tomography scans done early after stroke have limited ability to detect an acute ischemic lesion.f 25 lesions identified in 22 subjects.g Maximal axial diameter.




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ied depending on treatment groupassignment.

The overall emphasis of all treat-ments was task completion, andthere was no special emphasis topractice tasks focusing solely on im-proving speed, accuracy, or effi-ciency of movement. Further physi-cal therapy and occupationaltherapy after this 14-day period were

provided outside the clinical trial asconsidered necessary by each sub-

jects physician. Data in this reportare from the same cohort of subjects

with hemiparesis at 2 time points: aprerandomization baseline visit(acute time point: 8.73.6 days afterstroke) and a subacute follow-up

visit (subacute time point: 108.716.5 days after stroke). All data pre-

sented here were obtained fromexaminers who were masked totreatment group.

The age- and sex-matched controlsubjects (mean age59.1 years,SD12.5, range7078; 5 women,5 men) were free of neurologic ororthopedic conditions that might af-

fect their UEs. Subjects with hemi-paresis were tested twice, at anacute time point and at a subacutetime point. The control subjects

were tested once. Subjects with

hemiparesis were tested on their af-fected side (contralateral to the le-sion), and control subjects were

tested on their dominant side. Thedecision to test the dominant UE of

control subjects was made a priorias part of the VECTORS clinical trial.The motor task was a forward reach-ing movement and not a task thatinvolved hand dexterity, thus mini-mizing the possible influence ofhand dominance in our data. In-

formed consent was obtained fromall subjects prior to participation.

Measurement of reaching perfor-mance. Subjects were studied per-forming a forward reaching task

while seated in a straight-back chair.The trunk was stabilized to the backof the chair using a strap placed at

chest height to minimize compensa-tory trunk movements.14 The startposition (Fig. 1) was: UE resting on apillow on the ipsilateral thigh, withthe shoulder in approximately 0 de-grees of flexion and extension and 0degrees of internal rotation and withthe elbow in 75 to 90 degrees offlexion. The wrist rested palm down,

with the finger joints in slight flexionon the pillow. Minor modifications(eg, increased shoulder internal rota-tion) to the start position were al-lowed for some subjects to minimizeany positional discomfort.

Three-dimensional movements wererecorded at 60 Hz using a 6-camera

HiRes Motion Analysis Corporation(MAC) System.* A total of 13 reflec-tive markers were placed on thetrunk (3 markers), upper arm (3markers), forearm (3 markers), dor-sum of hand (1 marker), index finger(1 marker), thumb (1 marker), andtarget (1 marker). The resolution ofthe MAC system is 1 mm for a vol-

u m e of 1 m3 for marker position.Movements were recorded simulta-neously from each camera, and the

data were stored on a computer diskfor further analysis.

From the start position, subjectswere instructed to reach forward as

fast as possible and touch a 40-mmspherical target positioned 90% ofarms length directly in front of theaffected (dominant) shoulder atshoulder height. Subjects were given1 or 2 practice trials prior to record-ing to familiarize themselves with

the task and the instructions. Threetrials of reaching movement were re-corded. Data collection was limitedto 3 trials of reaching because thesubjects with hemiparesis fatiguedquickly, particularly at the acute

time point and because the subjectswere undergoing additional clinicalassessments in conjunction with

their participation in the VECTORSstudy.

Measurement of UE impairments.We measured sensorimotor impair-ments that are commonly assessedby physical therapists and occupa-tional therapists in stroke rehabilita-tion settings. Light touch sensation

was measured at 4 locations on thearm using Semmes-Weinstein mono-filaments. The smallest monofila-ment sensed at each location wasrecorded and given an ordinal scoreusing a previously described scale.33

Joint position sense was measured atthe first metacarpophalengeal jointfollowing standard clinical tech-

niques.34 Joint position sense wasscored as intact (correct responsein3 of 5 trials) or absent (correctresponse in 3 of 5 trials). Elbow

joint spasticity was measured usingthe Modified Ashworth Scale(MAS).35 Shoulder pain, as perceivedat the beginning of the testing ses-sion, was measured using a visual

analog scale.36

* Motion Analysis Corp, 3617 Westwind Blvd,Santa Rosa, CA 95403.

North Coast Medical, 18305 Sutter Blvd,Morgan Hill, CA 95037.

Figure 1.Schematic of reach movement start posi-tion and target.




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Maximal grip strength was measuredusing a Jamar handheld dynamome-ter. Strength of the shoulder, el-

bow, and wrist flexor and extensormuscle groups was measured bilater-

ally using a handheld dynamometer(MICROFET2) following a previ-ously described protocol37 exceptthat subjects were seated during test-ing. Maximal voluntary isometricstrength values were recorded (inpounds) for each muscle group

tested. Subjects who were unable toproduce force against the dynamom-eter were given a score of 0 lb forthat particular muscle group. Therelative strength of each musclegroup was calculated by taking the

ratio of the maximal isometric forceof the affected (nondominant) limbto the maximal isometric force of the

less-affected (dominant) limb.

To assess the ability make isolated(fractionated) UE movements, sub-

jects performed isolated flexion andextension movements of the shoul-der, elbow, and wrist joints while3-dimensional movements were re-corded in the same manner as during

the reaching task. The starting posi-tion for each isolated movement was

with the shoulder in 0 degrees offlexion and extension, with the el-bow extended and the wrist in neu-tral (ie, arm hanging by side). Forisolated shoulder movement, sub-

jects were instructed to flex theshoulder to 90 degrees while keep-

ing the elbow and wrist still. For iso-lated elbow movement, subjects

were instructed to maximally flexthe elbow while keeping the shoul-der and wrist still. For isolated wristmovement, subjects were instructedto extend the wrist while keepingthe shoulder and elbow still.

Data AnalysisOffline, EvaRT, and Kintrak soft-

ware* were used to extract position,

velocity, and angular data during thereaching task. Because of the redun-

dant camera system, no markerswere lost. Data were low-pass fil-tered at 6 Hz. For the reach, start ofmovement was defined as the timeat which the tangential wrist velocityexceeded 5% of maximum velocity.

End of the first phase of reach was

defined as the time at which thewrist velocity dropped to a mini-mum prior to subsequent correctivemovements. For each trial, we quan-tified the speed, accuracy, and effi-ciency of reaching3 characteristics

of performance that are importantfor normal function. We consideredan efficient reach to be one in which

the hand moves directly to the targetwithout extraneous or abnormallycircuitous movements.

Peak wrist velocity, endpoint error,and reach path ratio were used toquantify the speed, accuracy, and ef-ficiency of reach, respectively. Peak

wrist velocity was the maximum tan-

gential linear velocity of the wristattained between the start of move-ment and the end of the first phase ofreach. Endpoint error was the3-dimensional distance from the in-dex finger to the center of the targetat the end of the first phase of reach.Reach path ratio was calculated asthe ratio of the length of the actual

wrist path traveled to an idealstraight line between the start posi-tion and target touch. For subjects

who were unable to touch the tar-get, the reach path ratio was calcu-lated from start of movement to thetime and position where the indexfinger was closest to the target. Areach path ratio of 1 represents

a straight path (normal), whereas areach path ratio1 represents eitheran abnormally curved path or multi-ple attempts to touch the target. Inthis study, the reach path ratio waschosen as a measure of efficiency

because, in our subjects with hemi-paresis, higher reach path ratios

were due to multiple attempts to

touch the target and were not due todecoupling in the shoulder and el-

bow joint, as they are in subjectswith cerebellar damage.38 In addi-tion, the time from start of move-ment to target touch was calculatedand reported as movement time.

To quantify a subjects ability to per-

form isolated (fractionated) joint mo-tion, individuation indexes were cal-culated for the shoulder, elbow, and

wrist using the angular excursionsmeasured during the isolated move-ment tasks.33,39 41 The individuation

index is a measure of how well theinstructed joint is able to move byitself, without other joints moving.

The individuation index will be closeto 1 for an ideally isolated movementin which the instructed joint moved

with no movement at noninstructedjoints, and it will be closer to 0 themore the noninstructed jointsmoved with the instructed one. Sub-

jects who had little to no volitionalmovement, defined as less than 10%

of the control groups average angu-lar excursion, were given a score of0 for the individuation index for thatsegment. A composite individuationscore33was calculated as the averageof the individuation indexes for theshoulder, elbow, and wrist, whereeach joint was equally weighted. Thecomposite individuation score re-

flects the ability to make fractionatedUE movements (ie, move out of ste-reotypical synergistic patterns).33

Upper-extremity strength deficitswere quantified 3 ways. First, maxi-mal grip strength was used to quan-tify distal strength. Second, a com-posite UE strength score18 was

calculated because the strengthscores for the various muscle groups

were correlated with each other.Relative strength (the ratio of thestrength of the affected [nondomi-nant] limb to strength of the less-

Pro-Med Products Inc, 6445 Powers FerryRd, #199, Atlanta, GA 30339. Hoggan Health Industries, 8020 S 1300 West,

West Jordan, UT 84088.




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affected [dominant limb]) scores atthe shoulder, elbow, and wrist wereaveraged (equally weighted) to ob-

tain a composite UE strength scorefor each subject. Thus, the compos-

ite strength score reflects the distrib-uted isometric strength of the UE rel-ative to the nonparetic (dominant)side. This method was useful for sub-

jects who could produce forceagainst gravity and manual resis-tance but not for those subjects who

could move against gravity but wereunable to produce force against man-ual resistance (eg, a floor effect).

We therefore used measurements ofactive range of motion (AROM) as

our third way to quantify strength.42

The AROM at each joint was calcu-lated as the total average excursion

of the joint against gravity during theisolated movement tasks. Becausesubjects were instructed to flex theirshoulder to 90 degrees during theisolated movement task, maximumshoulder flexion values were limitedto 90 degrees. A composite AROMscore, reflecting the sum of the mea-surements of AROM at the shoulder,

elbow, and wrist, was calculated forsubsequent statistical analyses. The

AROM measurements of the shoul-der, elbow, and wrist were equally

weighted in the calculation of thecomposite AROM score because the

AROM measurements of the 3 jointswere significantly correlated witheach other. Composite AROM was

related to composite strength(r.45, P.05), supporting the useof AROM as a lower-end measure ofstrength.

A composite UE light touch sen-sation score was calculated by aver-aging (equally weighted) the ordinalscores from the 4 test sites because

strong correlations existed amongthe sites. Joint position sense wascoded for statistical analysis(present0 and absent1).

Statistica software was used for allstatistical analysis and the criterionfor significance as set at P.05. Dis-

tributions of variables were testedfor normality using the Shapiro-Wilk

W test. Some of the sensorimotorimpairment and kinematic variableswere not normally distributed andneeded to be transformed for furtherstatistical analyses. The type of trans-formation done on a variable waschosen by examining the raw distri-

bution and then selecting the trans-formation that would best minimizeskewness. Four sensorimotor impair-ment variables were transformed asfollows: composite strength usingthe natural log function, composite

AROM using the natural log function,composite individuation score usingthe natural log function, and the MAS

scores using percentile ranks. Twokinematic variables were trans-formed as follows: reach path ratioand end point error using the naturallog function. All statistical analyseson these 6 variables were done usingthe transformed data.

We used t tests to look for differ-

ences in reaching performance andcomposite measures of impairment(eg, composite UE strength) be-tween: (1) subjects with hemiparesisand control subjects and (2) the sub-acute and acute time points for thesubjects with hemiparesis. A seriesof 2 3 (time joint) repeated-measures analyses of variance

(ANOVAs) were used to test forchanges over time in individuation,

AROM, and UE strength in the sub-jects with hemiparesis. A series of2 3 (group joint) repeated-measures ANOVAs were used to testfor differences in individuation,

AROM, and UE strength between thesubjects with hemiparesis and the

control subjects at the 2 time points.Tukey Honestly Significant Differ-ence tests were used for post hoccomparisons when significant main

and interaction effects were present.Spearman rank order and Pearsonproduct moment correlations were

used to test for relationships be-tween the various sensorimotor im-

pairments as well as the relation-ships between reachingperformance and measures of UE im-pairment. Bonferroni corrections

were applied to adjust for multiplecomparisons.

Stepwise linear multiple regression,which predicts the maximumamount of variance (R2) with a min-imum number of independent vari-ables,43 was used as an exploratorytool to identify which sensorimotor

impairments were the strongest pre-dictors of reaching performance inthe early months after stroke. Specif-

ically, a series of forward stepwiselinear multiple regression analyses

were used to determine whether UEimpairments measured at the sub-acute time point could predict the

variance in the speed, accuracy, andefficiency of reaching performanceat the same time point and whetherUE impairments measured at the

acute time point could predict thevariance in the speed, accuracy, andefficiency of reaching performanceat the subacute time point.

ResultsThis article focuses on the recoveryfrom the acute time point to the sub-acute time point and on the status at

the subacute time point. Althoughdata from the acute time point(N46) are detailed elsewhere,18 asummary of findings from the acutetime point in the current cohort ofsubjects (N39) is provided to facil-itate comparisons.

Reaching Performance andSensorimotor Impairments at theAcute Time PointDuring the acute phase after stroke,reaching performance was generallypoor (black bars, Fig. 2), such thatthe subjects with hemiparesis had StatSoft Inc, 2300 E 14th St, Tulsa, OK 74104.




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longer movement times (P.002),lower peak wrist velocities(P.001), larger endpoint errors(P.001), and higher reach path ra-tios (P.02) compared with the con-

trol subjects. The hemiparetic sub-jects had deficits in all sensorimotormeasures at the acute time point(black bars, Fig. 3). Composite lighttouch sensation and joint positionsense were impaired in 59% and 33%of the subjects with hemiparesis, re-spectively. Forty-nine percent of thesubjects with hemiparesis had some

degree of elbow spasticity, but it wastypically mild (MAS score1).Twelve (31%) of the subjects withhemiparesis reported shoulder pain,

with 11 of those subjects reportingmild to moderate pain on the visual

analog scale (VAS score2 or 4). Thesubjects with hemiparesis had defi-cits in AROM (main effect for group:F11.47; df1,47; P.001),strength (main effect for group:

F45.90; df1,47; P.001), and theability to isolate (fractionate) move-ments (main effect for group:F13.14; df1,47; P.001) com-pared with the control subjects.

Changes in ReachingPerformance and SensorimotorImpairments From theAcute Time Point to theSubacute Time PointImprovements were noted in thesubjects with hemiparesis for allreach performance variables by thesubacute time point (blue bars,

Fig. 2). Movement time, endpoint er-ror, and reach path ratio were similarto those of the control subjects bythe subacute time point (P.09,

P.11, andP.29, respectively), but

peak wrist velocities remained im-paired in the subjects with hemi-paresis compared with the controlsubjects (P.001). Although bothgroups had similar variability in peak

wrist velocities, the variability inmovement times, endpoint errors,and reach path ratios were larger inthe subjects with hemiparesis than

in the control subjects.

Figure 3 shows the sensorimotor im-pairments in the subjects with hemi-paresis at the acute (black bars)and subacute (blue bars) time points.

Figure 2.Mean reaching performance values for the subjects with hemiparesis during the acute phase (black bars) and the subacute phase(blue bars) after stroke and for the control subjects (white bars) for (A) movement time, (B) peak wrist velocity, (C) endpoint error,and (D) reach path ratio. Error bars represent standard deviations. Note that the diameter of the spherical target was 40 mm, soendpoint errors around 2530 mm (20 mm radius 510 mm for finger width) mean the subject was touching the target. Asterisk

(*) indicates significantly different than control subjects (P

.05), dagger () indicates significantly different than acute time point(P.05).




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Figure 3.Mean values for the subjects with hemiparesis during the acute phase (black bars) and subacute phase (blue bars) after stroke and

for the control subjects (white bars) for (A) composite light touch sensation (LTS), (B) joint position sense, (C) Modified AshworthScale scores, (D) shoulder pain, (E) relative strength, (F) active range of motion (AROM), and (G) individuation indexes. Error barsrepresent standard deviations. Relative strength represents the ratio of involved limb/noninvolved limb maximal isometric force.

ADanterior deltoid muscle, BICbiceps brachii muscle, WEwrist extensors, STR-Ccomposite strength, Shldrshoulder,Compcomposite. Shoulder AROM through Wrist AROMAROM in degrees of shoulder flexion (range090), elbow flexion(0130), and wrist extension (050). Frequency distribution of the Modified Ashworth Scale scores and shoulder pain for thesubjects with hemiparesis.




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Where appropriate, measurement ofsensorimotor impairments for con-trol subjects also are shown (white

bars). The presence and severity ofsensorimotor impairment were gen-

erally reduced at the subacute timepoint compared with the acute timepoint, except for spasticity andshoulder pain. Composite lighttouch sensation (Fig. 3A) and jointposition sense (Fig. 3B) recoveredsuch that the subjects with hemi-

paresis did not significantly differfrom the control subjects at the sub-acute time point (P.12 and P.36,respectively). The severity of elbowspasticity as represented by MASscores (Fig. 3C) and shoulder pain

(Fig. 3D) in the subjects with hemi-paresis increased (worsened) fromthe acute time point to subacute

time point (P.01 and P.05, re-spectively). Improvements werenoted in AROM (main effect for time:F32.80; df1,38; P.001),strength (main effect for time:F30.58; df1,38; P.001), and iso-lated movement control (main effectfor time: F11.96; df1,38;

P.001) (Fig. 3EG). Recovery was

incomplete because deficits re-mained in AROM (main effect forgroup: F4.99; df1,47; P.03),strength (main effect for group:F5.50; df1,47; P.02), and iso-lated movement control (main effectfor group: F5.94; df1,47; P.02)in the subjects with hemiparesiscompared with the control subjects.

Relationships BetweenImpairments and ReachingDeficits at the SubacuteTime PointRelationships between sensorimotorimpairments and reaching perfor-mance at the subacute time point

were examined using Spearman cor-

relation coefficients (Tab. 2, toppanel). Based on our sample size,correlation coefficients greater than.31 were statistically significant atthe P.05 level. Composite UEstrength and composite AROM were

related to speed, accuracy, and effi-ciency of reaching such that thegreater the UE composite strengthand AROM, the faster, more accu-rate, and more efficient the reach.

All other sensorimotor impairments

were not significantly related toreaching performance.

Stepwise multiple linear regressionanalyses were performed to deter-mine which impairment variablesbest predicted variance in reachingperformance. The most parsimoni-ous combination of independent

variables was determined by first ex-amining the zero-order correlationmatrixes and then entering indepen-dent variables that had a zero-ordercorrelation of r.25 with reachingperformance. When available, com-

posite impairment variables were en-tered into the regression to optimizethe statistical analysis. Ultimately, 3independent variables (compositestrength, composite AROM, and theMAS scores) were selected for inclu-

sion in the model. Multicolinearity ineach regression equation was evalu-ated by calculating the tolerance ofeach independent variable,44 withthe results indicating acceptable lev-els of redundancy among the 3 inde-pendent variables.

At the subacute time point, 27% of

the variance in reaching speed waspredicted by composite strength(Tab. 3, middle panel), with no othersensorimotor impairments enteredinto the model. For reaching accu-racy, 15% of the variance was pre-

Table 2.Spearman Correlations Between Sensorimotor Impairments and ReachingPerformancea

Speed(Peak WristVelocity)

Accuracy(Endpoint Error)

Efficiency(Reach PathRatio)

Subacute impairments and

subacute performance

C-AROM .43* .19 .44*

C-STR .55* .34* .47*

C-II .21 .05 .01

Pain .16 .23 .10

C-LTS .01 .07 .19

MAS .17 .29 .29

JPS .09 .20 .20

Acute impairments and

subacute performance

C-AROM .35* .33* .40*

C-STR .15 .21 .39*

C-II .07 .09 .04

Pain .01 .14 .17

C-LTS .13 .19 .06

MAS .12 .26 .22

JPS .11 .06 .07

a C-AROMcomposite active range of motion, C-STRcomposite strength, C-IIcompositeindividuation, Painshoulder pain, C-LTScomposite light touch sensation, MASModified AshworthScale, JPSjoint position sense. Asterisk (*) indicates P.05.




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dicted by composite strength (11%)and MAS scores (4%). For reachingefficiency, 26% of the variance was

predicted by composite strength(24%) and MAS scores (2%). Thus, at

the subacute time point, sensori-motor impairments predicted only asmall amount of the variance inreaching performance, regardless of

which measure of performance wasused, and composite strength wasthe common contributing factor.

Relationships BetweenImpairments at the Acute TimePoint and Reaching Performanceat the Subacute Time PointRelationships between sensorimotor

impairments at the acute time pointand reaching performance at thesubacute time point were examined

using Spearman correlation coeffi-cients (Tab. 2, bottom panel). Com-posite AROM was related to thespeed, accuracy, and efficiency ofreaching such that the greater com-posite AROM at the acute time point,the faster, more accurate, and moreefficient the reach at the subacutetime point. Composite strength was

related to efficiency of reachingsuch that the greater the compositestrength at the acute time point, themore efficient the reach at the sub-acute time point. The other sensori-motor impairments measured at theacute time point were not signifi-cantly related to reaching perfor-mance at the subacute time point.

In general, the correlations betweensensorimotor impairments at theacute time point versus reaching per-formance at the subacute time point

were weaker than the correlationsfrom the same time point.

Regression analyses were performedto determine which impairment vari-

ables measured at the acute timepoint best predicted variance inreaching performance at the sub-acute time point. As above, compos-ite strength, composite AROM, andMAS scores were entered into the

Table 3.Summary of Forward Stepwise Linear Multiple Regression Analyses for PredictingReaching Performancea

Variable Peak WristVelocity

Endpoint Error Reach Path Ratio

Incremental R2 Incremental R2 Incremental R2

Acute impairments

predicting

variance in

reaching

performance at

acute time point

C-STR .0418

C-AROM .4553 .3947 .2437

MAS .0159

F ratiob 16.04 (2,36) 13.95 (2,36) 11.92 (1,37)

R2 .4712* .4365** .2437**

Subacute

impairments

predicting

variance in

reaching

performance at

subacute time

point

C-STR .2723 .1078 .2389

C-AROM

MAS .0436 .0259

F ratiob 13.85 (1,37) 3.21 (2,36) 6.48 (2,36)

R2 .2723** .1513* .2648**

Acute impairments

predicting

variance in

reaching

performance at

subacute time

point

C-STR .0280

C-AROM .1703 .1208 .1971

MAS .0394 .0273

F ratiob 7.59 (1,37) 3.43 (2,36) 3.94 (3,35)

R2 .1703** .1602* .2524*

a C-STRcomposite strength, C-AROMcomposite active range of motion, MASModified AshworthScale. Asterisk (*) indicates P.05, double asterisk (**) indicates P.01.b Degrees of freedom in parentheses.




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model. Seventeen percent of thevariance in reaching speed at thesubacute time point was predicted

by composite AROM values at theacute time point (Tab. 3, bottom

panel), with no other sensorimotorimpairment entered into the model.Sixteen percent of the variance inreaching accuracy at the subacutetime point was predicted by compos-ite AROM (12%) and MAS scores(4%) at the acute time point. Twenty-

five percent of the variance in reach-ing efficiency at the subacute timepoint was predicted by composite

AROM (19%), composite strength(3%), and MAS scores (3%) at theacute time point. Thus, sensorimotor

impairments measured at the acutetime point predicted only a smallportion of the variance in reaching

performance at the subacute timepoint, regardless of which character-istic of movement performance wasused as the dependent variable.

Do Sensorimotor ImpairmentsPredict Greater Proportions ofVariance for UE Function Thanfor Specific Characteristics of

Motor Performance?We chose reaching as a representa-tive movement task, yet reaching isonly one movement in an enormousrepertoire of possible UE move-ments. To determine whether therelatively limited predictive value ofsensorimotor impairments was dueto selecting a single movement task,

we performed additional regressionanalyses in which the ARAT scores

were entered into the regression asthe dependent variable in lieu ofpeak wrist velocity, end point error,and reach path ratio (Tab. 4). The

ARAT is a functional assessment ofUE movement across a range ofmovement tasks (ie, gross movement,

grasping, gripping, and pinching).

At the acute time point, sensorimo-tor impairments predicted 43% ofthe variance in ARAT scores, a pre-dicted variance similar to that for the

models using reaching speed and ac-curacy (Tab. 3, top panel). At thesubacute time point, sensorimotorimpairments predicted 57% of the

variance in ARAT scores, a predictedvariance that was twice as large asthat for the models using reachingspeed, accuracy, and efficiency. Sen-sorimotor impairments measured atthe acute time point predicted 38%of the variance in ARAT scores atthe subacute time point, a predicted

variance that was somewhat larger

than that for the models using reach-ing speed, accuracy, and efficiency.Thus, sensorimotor impairments pre-dict similar or greater proportionsof variance for UE function thanfor specific characteristics of a single

motor task during the first fewmonths after stroke.

Contribution of Grip StrengthImpairment to the Variance inReaching PerformanceGrip strength has been proposed asa surrogate marker for recovery ofUE function after stroke.4,7,10 Inour sample, grip strength measure-ments were correlated to compositestrength measurements at the acutetime point (r.69, P.05) and at the

subacute time point (r.76, P.05).At both acute and subacute timepoints, grip strength was related tospeed (r.47 and r.58, respec-tively) and accuracy (r.44 andr.44, respectively) of reaching

Table 4.Summary of Forward Stepwise Linear Multiple Regression Analyses for Predicting

Action Research Arm Test (ARAT) Scoresa

Variable Incremental R2

Acute impairments predicting variance in ARAT scores at acute time

point

C-STR .3155

C-AROM .0250

MAS .0906

F ratiob 8.84 (3,35)

R2 .4311*

Subacute impairments predicting variance in ARAT scores at

subacute time point

C-STR .0127

C-AROM .5560

MASF ratiob 23.73 (2,36)

R2 .5687*

Acute impairments predicting variance in ARAT scores at subacute

time point

C-STR .0181

C-ROM .3597

MAS

F ratiob 10.93 (2,36)

R2 .3778*

a

C-STR

composite strength, C-AROM

composite active range of motion, MAS

Modified AshworthScale. Asterisk (*) indicates P.01.b Degrees of freedom in parentheses




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such that a greater grip strength wasassociated with a faster and moreaccurate reach. At the subacute time

point, grip strength also as related toefficiency of reaching (r.37)

such that greater grip strength wasassociated with a more efficientreach.

To determine whether grip strengthwas a better predictor of the vari-ance in reaching performance than

our composite UE strength measure,we performed additional regressionanalyses in which grip strengthscores were entered as an indepen-dent variable in lieu of UE compositestrength. Entering grip strength mea-

sured at the subacute time point asan independent variable to predictthe variance in reaching perfor-

mance at the subacute time point,the amounts of explained variance inpeak wrist velocity, endpoint error,and reach path ratio were 33%, 9%,and 22%, respectively. Entering gripstrength measured at the acute timepoint to predict the variance inreaching performance at the sub-acute time point, the amounts of ex-

plained variance in peak wrist veloc-ity, endpoint error, and reach pathratio were 17%, 16%, and 25%, re-spectively. Thus, the same amount of

variance in reaching performancewas explained whether grip strengthor composite UE composite strength

was entered into the regressionmodel.

DiscussionOur results show that the proportionof variance explained in reachingperformance by sensorimotor im-pairments is variable depending onthe predicted characteristic of move-ment (speed, accuracy, or effi-ciency), the chronicity of hemipare-

sis, and the duration of time betweenthe assessment of sensorimotor im-pairment and motor performance.The greatest amount of variance inreaching performance was ex-plained at the acute time point by

sensorimotor impairments at theacute time point. Only a smallamount of variance in reaching per-

formance (30%) was explained atthe subacute time point, using either

acute or subacute sensorimotor im-pairments as predictor variables.

To our knowledge, this is the firststudy to examine specific character-istics of movement performance dur-ing a functional UE task to assess

motor recovery during the acute andsubacute phases after stroke. Studiesthat have predicted motor recoveryfollowing stroke have primarily usedclinical measures of UE motor perfor-mance,2,69,13 UE functional recov-

ery,10,11,13,45 or global disability1 asthe measure of motor recovery. Wechose to study specific characteris-

tics of reaching instead of clinicalmeasures of motor and functionalperformance as markers of motor re-covery because we believed that abetter understanding of the charac-teristics of functional movement(timeliness, accuracy, efficiency)

will provide additional insight aboutcentral nervous system control of

movement after stroke, while pro-viding clinicians with informationthat may help guide the selection ofrehabilitation techniques and exer-cise parameters (eg, focusing onstrength to improve speed ofmovement).

Reaching performance of the sub-

jects with hemiparesis recoveredsuch that only peak wrist velocitysignificantly differed between thesubjects with hemiparesis and thecontrol subjects. The improvementof reaching accuracy and efficiency

was accompanied by a decline in thepresence and severity of the majorityof sensorimotor impairments; how-

ever, sensorimotor impairment re-covery was incomplete becausethere were persistent deficits instrength, AROM, and isolated move-ment control, as well as increased

elbow spasticity and shoulder pain atthe subacute time point (Fig. 3).

Two interpretations of these findingsare relevant to clinicians and scien-

tists interested in UE motor recoveryfollowing stroke. First, our resultsimply that the performance of a func-tional movement can be normal ornear-normal despite the presence ofunderlying sensorimotor impair-ments. This may reflect the idea that

not all functional movements requirefull sensorimotor capacity. For exam-ple, our subjects with hemiparesis

were able to meet the sensorimotorrequirements of the reaching task de-spite the presence of measurable

sensorimotor impairments. Our con-trol subjects used approximately 35degrees of shoulder flexion, 15 de-

grees of elbow flexion, and 10 de-grees of wrist extension to reach thetarget. These values are within therange of available AROM for the sub-

jects with hemiparesis (Fig. 3), sug-gesting that, despite limitations inmaximal AROM, subjects with hemi-paresis were able to meet the AROMdemands of the reaching task. Sec-

ond, our results imply that the nor-malization of specific characteristicsof reaching (ie, accuracy, efficiency)does not indicate full UE sensori-motor recovery, suggesting that ki-nematic analyses of UE movementmay not adequately describe motorrecovery following stroke. Addi-tional research is needed to deter-

mine which outcome measure (ie,kinematic variable versus standard-ized clinical examinations), or com-bination of measures, best reflectsUE motor recovery following stroke.

Sensorimotor impairments predictedsimilar amounts of variance(R243%) for ARAT scores and 2 of

the 3 characteristics of reaching(speed and accuracy) at the acutetime point; however, by the sub-acute time point, sensorimotor im-pairments predicted approximatelytwice the amount of variance in




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ARAT scores (R2.57) than forspeed and accuracy of reaching(R2.27 and R2.15, respectively).

These findings indicate that clinicalmeasures of sensorimotor impair-

ments are more predictive of thevariance in UE function (eg, ARATscores) than for a single functionalmotor task at the subacute phase.The subacute time point is the time

when our subjects were living intheir homes and interacting with

their communities. One explana-tion for this outcome may be that,during the early days after stroke,

when UE use is limited,46 a fewmovement tasks (eg, reaching) aresufficient to assess motor control of

the UE, but later in the course ofrecovery, as movement capacity andcomplexity increase, more motor

tasks are needed to capture the mo-tor performance of the UE. Futurestudies are needed to investigatehow sensorimotor impairmentsmay or may not contribute to UEactivity and participation outsidethe hospital, clinic, or laboratoryenvironment.

We believe it is noteworthy thatsensorimotor impairments, whethermeasured at the acute time point orthe subacute time point, were notfound to be strong predictors of the

variance in speed, accuracy, or effi-ciency of reaching at the subacutephase after stroke. Thus, our detailedclinical examination of sensorimotor

status (an examination that is moredetailed than done typically at bed-side) did not adequately capture the

variance of a common functionalmotor task.

One explanation for the low amountof explained variance is that thesensorimotor impairments evaluated

during a typical examination arelacking (ie, some potentially impor-tant impairments that may predicthow people perform functionalmovements are missing). For exam-ple, as is typically done bedside,

strength was evaluated isometricallywith one contraction of each musclegroup, but it may be that more dy-

namic assessments of concentric andeccentric muscle strength and mus-

cle power (eg, via isokinetic testing)or assessments of muscle enduranceare more informative. Other poten-tially important impairments that

were not assessed include deficits inmotor planning and non-motor fac-tors (ie, attention deficits, depres-

sion). Further research is needed toevaluate the importance of theseother factors for predicting the vari-ance in UE motor performance inpeople with poststroke hemiparesis.

It is possible that the limited predic-tive ability of our model (R2.57)

was due to using multiple linear re-

gression analyses (MRA) to predictthe variance of complex motor tasks(ie, reaching performance and motorfunction as assessed by the ARAT).In MRAs, the proportion of total vari-ance explained in the dependent

variable is contingent upon the par-ticular set of independent variablesused in the analysis, and the number

of independent variables is con-strained as a function of sample size,

where it is generally recommendedthat there should be 10 to 20 sub-

jects per predictor variable. Due toour sample size (N39) we were re-stricted to about 4 predictor vari-ables. We considered both samplesize and zero-order correlations

when selecting the 3 independentvariables (composite strength or gripstrength, composite AROM, MASscores) for our MRAs. It is possiblethat a larger proportion of variancecould have been explained for thesecomplex motor tasks if different oradditional independent variables hadbeen entered into the model. Further

research, with larger sample sizes, isneeded to determine whether othercombinations of independent vari-ables yield larger proportions of ex-plained variance for these complexmotor tasks.

It is possible that the low amount ofvariance explained by our modelwas due to using linear multiple re-

gression to predict the variance inmotor performance, when the rela-

tionships between sensorimotor im-pairments and reaching performancemay have been better captured by anonlinear regression model. Al-though we cannot rule out this pos-sibility, it is unlikely that a nonlinearmodel would have been a better fit

because visual inspection of scatterplots did not reveal curvilinear rela-tionships between individual senso-rimotor impairments and reachingperformance or ARAT scores.

Regardless of whether movementperformance was quantified asspeed, accuracy, or efficiency, UE

strength deficits, as measured bycomposite AROM or compositestrength, were the most commonpredictors of the variance in reach-ing performance during the first 3months after stroke. These resultsare consistent with previous reportslinking the severity of UE weakness

with the outcome of UE movement

and function.6,7,9-11,45,47,48

Maximal isometric grip strength wasfound to be as strong as a predictoras a composite measure of UE iso-metric strength for predicting reach-ing performance at the acute andsubacute time points. These resultssuggest that future studies of reach-

ing performance could be more effi-ciently conducted by obtaining gripstrength measures in lieu of maximalisometric strength testing. Additionalresearch is needed to determine

whether maximal grip strength is agood proxy for other strength met-rics (ie, maximal dynamic peaktorque) or whether equivalent re-

sults would be found when studyingother UE tasks.

The ability to isolate (fractionate)movement, as measured by individu-ation indexes, was not a significant




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predictor of the variance in peakwrist velocity, endpoint error, orreach path ratio in our cohort of

subjects at both acute and subacutetime points. These results differ from

those of a report of patients withchronic hemiparesis,33 where indi-viduation indexes, not strength,were the best predictors of reachpath and endpoint error. We postu-late that the different relationshipsobserved between reaching perfor-

mance and sensorimotor impair-ments in our subjects with acute orsubacute hemiparesis versus the pa-tients with chronic hemiparesis maybe linked to the disparity in the chro-nicity of hemiparesis between the

groups (subacute hemiparesis10917 days poststroke, chronichemiparesis3262 months post-

stroke). One possible explanation isthat, in the chronic phase afterstroke, spared components of the de-scending motor system may havebeen able to activate motor units toproduce force, but may not havebeen able to activate them selec-tively. Thus, poor isolated move-ment control (ie, the inability to

move out of stereotypic synergies)may limit motor performance morethan strength deficits in people withchronic hemiparesis.

Our subjects represent a subset ofpatients with stroke and were se-lected based on the presence ofhemiparesis. Although our subjects

are reasonably representative of sub-jects with poststroke hemiparesisseen in inpatient rehabilitation facil-ities in the United States, they appearto be less severely affected overallthan the subjects often used to ex-amine movement control in people

with chronic hemiparesis.14,22,24,49,50

For example, 33% (13/39) of our sub-

jects at the subacute time point hada maximum score of 57/57 on the

ARAT. Caution should be takenwhen interpreting the present re-sults with respect to previous workbecause the same movement control

problems may not be present in sub-jects with mild-to-moderate hemi-paresis compared with subjects with

more severe hemiparesis.24

ConclusionsOur data demonstrate that the rela-tionships between sensorimotor im-pairments and specific characteris-tics of movement performance aredynamic during the first few monthsafter stroke and that common clini-cal measures of sensorimotor impair-ment, measured at the acute or sub-

acute phase after stroke, do notpredict large proportions of variancein reaching performance during thesubacute phase after stroke. Our data

suggest a potential limitation in theuse of kinematic variables for the as-sessment of sensorimotor recoveryfollowing stroke. Of the sensori-motor impairments, strength, as

measured by composite isometricstrength, grip strength, or composite

AROM, was the strongest and mostconsistent predictor of the variancein reaching performance or motorrecovery.

Dr Wagner, Dr Lang, Dr Sahrmann, and DrDromerick provided concept/idea, researchdesign. Dr Wagner and Dr Lang providedwriting. Dr Wagner, Dr Edwards, and DrDromerick provided data collection. DrWagner, Dr Lang, Dr Edwards, and Dr Dro-merick provided data analysis. Dr Wagner,Dr Lang, and Dr Dromerick provided projectmanagement. Dr Dromerick provided fundprocurement and subjects. Dr Lang and DrDromerick provided facilities/equipment.Dr Dromerick provided institutional liaisons.Dr Wagner provided clerical support. DrWagner, Dr Lang, Dr Sahrmann, and Dr Ed-

wards provided consultation (including re-view of manuscript before submission). Theauthors thank Lily Hu for her assistance withdata collection and processing and LucyMorris, MD, MPH, for her assistance with thelesion data analyses. They also thank the par-ticipants and the therapists who assistedwith recruitment and scheduling during thisproject.

The study was approved by the InstitutionalReview Board at Washington UniversitySchool of Medicine.

This work, in part, was presented at theCombined Sections Meeting of the Ameri-can Physical Therapy Association; February15, 2006; San Diego, Calif.

This work was supportedby National Institutes of

Health grants NS41261and HD047669, James S.

McDonnell Foundation grant 21002032,andthe Foundation for Physical Therapy Pro-motion of Doctoral Studies Scholarship.

This article was received May 5, 2006, and

was accepted January 30, 2007.

DOI: 10.2522/ptj.20060135

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7/30/2019 Phys Ther 2007 Wagner 751 65

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doi: 10.2522/ptj.20060135

Originally published online April 18, 20072007; 87:751-765.PHYS THER.

DromerickSahrmann, Dorothy F Edwards and Alexander WJoanne M Wagner, Catherine E Lang, Shirley ARecoveryHemiparesis During the First Few Months ofPerformance in Subjects With PoststrokeSensorimotor Impairments and Reaching

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