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TRANSLATIONAL PHYSIOLOGY
1Department of Mechanical Engineering and 2School of Rehabilitation Sciences, University of British Columbia; and 3Rehab Research Laboratory, GF Strong Rehabilitation Centre, Vancouver, British Columbia, Canada
Submitted 19 July 2004; accepted in final form 8 July 2005
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
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). Reaching function is critical to daily activities (Granger et al. 1986) and, in persons with stroke, its performance is strongly correlated with upper extremity impairment (e.g., Kamper et al. 2002; Levin 1996; Lum et al. 1999).
Reaching is a task of motor abundance as the number of joints available for movement and their coordination is unrestricted (Bernstein 1967). Despite the infinite number of possible movement patterns, hand and joint motions are similar across the healthy population (Kaminski et al. 1995). Joint abundance provides the functional ability to control movements adaptively to account for both environmental factors and internal constraints, such as injury (Latash 1996). Impairments that may potentially constrain reaching performance after stroke include altered intersegmental dynamics (Beer et al. 2000), impaired sensation (Zackowski et al. 2004), spasticity (Levin 1996), and muscle weakness (Mercier and Bourbonnais 2004). It is known that constraints from stroke impairments can result in the need for additional degrees of freedom at other joints such as movement compensations of the trunk during reaching (Cirstea and Levin 2000).
The gravitational forces during reaching to an elevated target are particularly challenging for individuals with stroke (Reinkensmeyer et al. 1999). We believe these demands would require compensations such as altered muscle activation. In fact, Trombly et al. (1992) suggested that individuals with stroke use a higher fraction of their maximum muscle activity with their paretic (vs. nonparetic) arm during reaching. Because their results were inconclusive with a small sample (n = 5), we propose to test whether paretic muscles approach saturation (i.e., muscle activity approaches capacity). We also postulated that a saturation of muscle activation is related to muscle weakness and that saturation would require recruitment of additional muscles, resulting in movements out of the sagittal plane. Such a hypothesis is driven by clinical observations that individuals with stroke often use stereotypical out-of-plane reaching movement strategies (Carr and Shepherd 1999).
Dynamic analyses in the lower extremity have elucidated a number of compensatory kinematic and kinetic movement strategies during gait after stroke (de Quervain et al. 1996). For example, increased hip abduction power (i.e., hip hiking) of the paretic limb can compensate for deficits in ankle plantarflexion push-off to preserve functional gait (Kim and Eng 2004). Such nonsagittal compensations have yet to be analyzed for reaching movements. We hypothesized that age-matched controls would perform reaching movements primarily in the sagittal plane because task-appropriate muscles are used substantially below capacity. Conversely, we hypothesized that the paretic arm of individuals with stroke would demonstrate saturation of their muscle activity during the reaching activity and require recruitment (compensation) from other muscles resulting in out-of-plane components during the task.
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METHODS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
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Twenty older adults (age: mean = 60.9, SD = 6.1, range = 49–72 yr; sex: 13 males and seven females) were recruited from the community with the following inclusion criteria: 1) a minimum of 1 yrpoststroke, 2) present with hemiparesis secondary to first cerebrovascular accident (CVA), 3) able to provide informed consent, 4) able to follow one- and two-step commands, and 5) able to voluntarily flex/abduct their shoulder 45° and extend their elbow 120°. None of the subjects with stroke presented with hemispatial neglect (Schenkenberg et al. 1980). Ten right-handed healthy adults of similar age (mean = 61.0, SD = 9.0, range = 51–77 yr) and gender (six males and four females) were recruited from the community to serve as the control group. Musculoskeletal or neurological conditions (in addition to the CVA for the stroke participants) that would affect arm function were exclusion criteria for all participants. The characteristics of the participants with stroke are described in Table 1. To identify stroke-induced changes to reaching performance, we used the nondominant arm of healthy subjects for comparison ("control condition"). Because our central purpose was to identify the effect of stroke on reaching performance, we used only the nondominant arm of control subjects for comparison. Motor control of the dominant arm is superior to the nondominant arm in healthy individuals (Sainburg and Kalakanis 2000) so this represented a conservative approach of identifying stroke-related deficits. Local university and hospital ethics committees approved the study protocol.
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) and by the Modified Ashworth Scale (MAS) for hypertonia (Bohannon and Smith 1987) (0 = no increase in muscle tone; 4 = rigid). Twelve participants with stroke were evaluated a second time 2 to 3 days after the first assessment to establish intersession reliability. Experimental setup
Participants sat in a chair with their arm relaxed and their hand resting on their ipsilateral thigh (i.e., shoulder adducted, elbow in midflexion, and forearm pronated) and reached to a shoulder height target (i.e., glenohumeral joint). Active range of motion was assessed while the subject was in the experimental setup and the target (3 x 3-cm square) was located just inside the workspace limits of the paretic arm of the subjects with stroke or the nondominant arm of the control subjects. Thus the target distance was identical for the paretic and nonparetic arm of the subjects with stroke. The horizontal forward distance (shoulder to finger tip) was a mean of 66.3 cm (min = 59.4, max = 74.7) for the control group and 56.2 cm (min = 39.5, max = 76.9) for the stroke group.
Participants performed five unconstrained reaching movements to the target. For each trial, participants started in a relaxed state and were instructed: "At the sound of the tone (an auditory cue), reach and touch the target at as fast as possible." Participants touched the target with their pointing finger (index finger tip or index distal interphalangeal joint if unable to extend the interphalangeal joint). Crossing lap belts (extending from just above the shoulder to the opposite hip) supported the torso to prevent trunk and hip movement.
Participants also performed three isometric maximal voluntary contractions (MVCs) of upper extremity movements (shoulder flexion, extension, abduction, adduction, internal and external rotation, and elbow flexion and extension) in midrange using the isometric mode of a dynamometer system (KinCom, Chattanooga, TN). The isometric protocol has been described in detail previously (McCrea et al. 2003).
Data collection
Three noncollinear infrared emitting diodes (IREDs) were placed on each upper limb segment (hand, forearm, and upper arm) and registered relative to anatomical landmarks. IRED movements were tracked by an optoelectronic sensor (Northern Digital Optotrak) at 60 Hz and then filtered using a second-order Butterworth low-pass filter at 10 Hz. All movements were represented in terms of the right arm (left arm movements were reflected across the midsagittal plane). Movement initiation and cessation were identified from the tangential velocity profile of an IRED attached to the pointer (i.e., tip of index finger). Movement began and terminated when the tangential velocity rose above and fell below 5% of the peak velocity (relative to zero baseline).
Muscle activation was recorded during the reaching movement by surface electrodes (self-adhesive, silver, silver-chloride pellet electrodes with 7-mm diameter, fixed interelectrode distance of 30 mm; Kendall Meditrace, Chicopee, MA) placed on the anterior and lateral heads of the deltoid, the long head of the triceps, the biceps brachium, and the brachioradialis. Electromyograms (EMGs) were collected (Bortec Electronics, Calgary, Canada), converted analog to digital (600 Hz) (AT-MIO-64E-3, National Instruments, Austin, TX), and low-pass filtered at 100 Hz. EMG was also recorded during MVCs, along with the peak torque. The isometric protocol has been reported previously (McCrea et al. 2003).
Neuromuscular force and activity
EMG profiles were converted to a time base of 0 to 100% of movement. For each muscle, the mean EMG during reaching was normalized by the EMG at MVC to quantify saturation (i.e., % muscle use). The peak torque during the MVC was also recorded to provide an indication of muscle strength.
Joint configuration and mechanics
Right-handed coordinate systems (direction of axes in anatomical position: X = medial–lateral, Y = posterior–anterior, Z = inferior–superior) were embedded within each segment and rigid body calculations were used to track their global position and location on a frame-by-frame basis. Local joint angles, velocities, moments, and powers were described as the relative motion of the distal segment to the more proximal segment. The observed joint angles were computed using a Euler sequence: rotation 1 about the X-axis is a pure flexion/extension movement, rotation 2 about the Y'-axis is an adduction/abduction movement, and rotation 3 about the Z'' axis is a pure rotation about the longitudinal internal–external movement. These angles are referred to as 
, 
, and 
and correspond approximately to clinical descriptions of flexion/extension, adduction/abduction, and internal/external rotation angles; they have previously been used to describe motions in the upper extremity (Prokopenko et al. 2001). Euler sequences describe the rotations of a set of three joints in a fictitious mechanism that represents the three degrees of rotational freedom allowed at the shoulder joint. At each point in time, the current orientation of the humerus was represented by a Euler angle sequence (note that Euler angles represent instantaneous orientation and do not imply that the humerus has gone through any particular temporal sequence of rotations).
Limb inertias were estimated by using anthropometric tables by Yeadon and Morlock (1989). Muscle joint moments were calculated by a recursive Newton–Euler method (Meglan 1991). Mechanical powers were computed as the dot product of joint moments and velocities and represented about each rotational axis (i.e., flexor/extensor power, adductor/abductor power, and internal/external rotation power). For peak powers, positive power represents a generation of energy resulting from a concentric contraction, whereas negative power represents absorption of energy resulting from an eccentric contraction. Moment and power analyses during reaching have previously been shown to be sensitive indicators of neurological impairment (e.g., Riener and Straube 1997).
Preliminary inspection of profiles indicated that, regardless of arm condition (paretic, nonparetic, control), reaching tasks were executed without rotations of the wrist or forearm (in part, because our task did not require a specific hand orientation). Subsequent analyses were thus restricted to flexion–extension of the elbow and the three rotational axes of the shoulder. To facilitate comparisons between subjects, all profiles were converted to a time base that extended from 0 to 100% of movement; kinetic profiles (i.e., powers and moments) were additionally normalized by subject mass. From individual profiles we calculated mechanical effort (peak powers) and change in arm positioning (change in joint angles). For each trial, reaching strategies were determined by analyzing the patterns of joint trajectories (or bursts in the case of power profiles).
Hand path and trajectory
Kinematic descriptors of pointer movement were derived from path and trajectory profiles of each trial. Path directness, the ratio of the direct to the actual path length (Bastian et al. 1996), quantified the ability to execute a straight-line path. Segmentation and skewness parameters described the tangential velocity profile. Segmentation is a count of velocity peaks and is proposed to relate to the number of motor commands required to execute a movement (Krebs et al. 1999). More specifically, our segmentation algorithm identified peaks as local maxima separated by 
100 ms (i.e., <10 Hz). A statistical definition of skewness (Zar 1999) measured the central tendency of the velocity profile. A velocity profile becomes asymmetric and positively skewed (i.e., peaks occur earlier) when accuracy requirements necessitate a controlled deceleration.
Analyses
Analyses were performed on the mean values (across trials) of hand path/trajectory, joint configuration, peak power, and muscle activation parameters. The parameters indicated generally excellent relative [intraclass correlations, ICC(1,1) (Shrout and Fleiss 1979)] and absolute [SE, expressed as a percentage of the mean (Eliasziw et al. 1994)] reliability across two testing sessions. The exception (removed from further analyses because of poor reliability) was brachioradialis activation of the paretic arm. For other parameters, ICCs ranged from 0.74 to 0.96 (mean 0.87) in the paretic arm and from 0.64 to 0.96 (mean 0.80) in the nonparetic arm; SEs ranged from 1.1 to 31.6 (mean 15.3) % in the paretic arm and from 4.1 to 33.5 (mean 16.9) % in the nonparetic arm. All subsequent analyses used parameter values from the first day.
MANOVAs were used to assess the effect of arm condition (paretic, nonparetic, control) on hand path/trajectory, joint configuration, kinetic, and muscle use parameters with post hoc ANOVAs and Duncan’s comparison tests to identify differences among arm conditions. The combined use of multivariate and univariate analyses allowed for global protection of type I error while maintaining the ability to identify differences within individual parameters (Zar 1999); multivariate F and Wilks ’ Lambda were calculated for MANOVAs (Zar 1999).
To determine the contribution of muscle strength, we correlated the percentage of muscle use over the reaching task with the peak normalized isometric torque of their primary joint actions (e.g., anterior deltoid muscle use with shoulder flexion torque). In the paretic condition, Pearson correlations evaluated relations of motor impairment (Fugl-Meyer) against each parameter.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
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Muscle activity patterns were similar across the control subjects and unaltered by ensemble averaging (i.e., the defining characteristics of the curve still occurred at specific times and with similar amplitudes) (see Fig. 1). Consistent with previous studies of reaching in three dimensions (Flanders 1991) and the sagittal plane (Flanders et al. 1996), deltoid activity was characterized by phasic bursts occurring early and late in movement and by increased activity at movement termination; the magnitude of the EMG activities was largest for the anterior head and smallest for the lateral head. The same activation pattern was shared by biceps brachii. Triceps (long head) activity was characterized by a single burst occurring midway throughout movement. Activation patterns for the nonparetic arm condition were similar to those of the control condition.
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Kinetics
Shoulder moment of the control condition was predominantly flexor. In the early phase of movement, this moment arose primarily from joint acceleration and then asymptotically approached a value that was largely determined by the gravitational moment of the arm. The moment at the elbow was always flexor, increasing during elbow flexion (peak at about 15–30% of movement time) and decreasing during elbow extension. Moment profiles of the less affected arm condition were qualitatively similar to those of the arm of the control condition. In the more affected arm condition, there was a reduced flexor moment that coincided with a large increase in abduction moment; this compensation was particularly evident early in the movement profile. The flexor–extensor moment pattern of the elbow was similar to the control and nonparetic arm conditions, but more variable. Internal–external moment profiles of all arm conditions were biphasic (first internal then external) but were small in magnitude.
Shoulder power in the nonparetic and control conditions (see Fig. 2) was primarily flexor and concentric (generation) in origin with a peak occurring slightly after the midpoint of movement. Elbow power was biphasic and, as expected, primarily along the flexion–extension axis; this power was initially concentric (generation) as the elbow was flexed but eccentric (absorption) as the elbow extended under the force of gravity. There was a large increase in abductor generation power for the paretic arm condition that coincided with a large reduction in flexor generation power; 15 of the 20 subjects with stroke demonstrated greater than the maximum abductor power observed in control subjects. Elbow power remained biphasic in the paretic arm but with substantially reduced generation and absorption peaks.
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In the control arm condition, the upper arm was raised using primarily shoulder flexion (see Fig. 3). Shoulder flexion was consistently coupled with small increases (0–15°) in the abduction angle early in movement and decreases (about 0–10°) in the abduction angle late in movement. Internal–external rotation was always small, variable in direction, and not generally coupled with shoulder flexion. Elbow movement was consistently biphasic with slight flexion (5–15°) occurring early and extension (10–40°) near the end of the movement. Movements of the nonparetic arm were qualitatively similar to those of the control condition.
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The net angular change (i.e., initial to final) for shoulder flexion and elbow extension were prespecified by the required endpoint position of the task and thus not analyzed. Changes in abduction and internal rotation angles were affected by arm condition [Wilks’ Lambda statistic of 0.519, P < 0.05, F(4,92) = 5.19, P < 0.001] and highly correlated to severity of impairment in the paretic arm (see Table 4). There was also a significant increase in maximum abduction angle for the nonparetic arm condition versus the control condition.
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In both the control and nonparetic arm conditions (but not the paretic) the path was slightly curved and the velocity profile was substantially bell shaped (see Fig. 4). Kinematic descriptors of the hand path, particularly the directness parameter, were significantly affected by arm condition [Wilks’ Lambda statistic of 0.565, P < 0.05; F(6,90) = 3.47, P = 0.002] and correlated with the severity of impairment for the paretic arm condition (see Table 5).
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONGRANTSACKNOWLEDGMENTSREFERENCES |
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Successful completion of reaching tasks in this study required a specific positioning of the hand (i.e., target) at the end of movement but not a specific positioning of arm joints. Moreover, the CNS was free to use any hand and joint motions between start and end postures. With the initial posture of the upper limb in the same parasagittal plane formed by the targets and starting position, reaching tasks could have been accomplished entirely through shoulder flexion and elbow extension. The net joint movement (i.e., stop–start) of the control subjects was consistent with this prediction. However, the elbow flexion that preceded the required elbow extension suggests that the control of joint motion is not strictly predicted by external spatial factors. Early elbow flexion is advantageous because it initially reduces the lever distance between the shoulder and arm center of arm mass that, in turn, reduces required shoulder flexor moments, powers, and total energy. This strategy of flexing (before extending) the elbow and keeping the arm within the sagittal plane resulted in direct, nonsegmented, and symmetric hand motion in the control group and is consistent with a minimization of mechanical energy and thus muscular consumption of metabolic energy (Hogan 1984).
Stereotypical compensatory movement strategy in the paretic arm condition
Despite the abundant mechanical degrees of freedom available in the arm and heterogeneity of the lesion type, side, location, and resulting impairment of the subjects, compensatory movements were stereotypical and described by increasing abduction and internal rotation related to severity of impairment in the paretic arm. Reduced agonist recruitment capacity, as a consequence of stroke, can prevent the completion of upper extremity tasks (Gowland et al. 1992). Similarly, our results indicate that muscle weakness constrains the movement patterns available to the CNS because primary agonist muscles alone are not capable of generating the required execution torques. Second, they suggest that compensatory movements can occur by the recruitment of additional agonist muscles, thereby distributing the muscle force. In our reaching task, for example, the anterior deltoid was maximally activated (i.e., saturated) and flexor power substantially reduced, and thus increased abductor power generation and increased activation of the lateral deltoid were necessary to achieve the task. Note that the compensation for the anterior deltoid is task specific and is observed because the anterior deltoid is the primary mover for the reaching task; the compensation does not specifically occur because the anterior deltoid might have greater deficits than the other upper extremity muscles. This suggests that persons with stroke may also exhibit stereotypical compensations for other movements, despite the fact that patterns of weakness may vary across subjects with stroke (Colebatch and Gandevia 1989; McCrea et al. 2003; Mercier and Bourbonnais 2004). This is supported by observations that the directional ranges of individual muscles in the paretic arm broaden after stroke (i.e., muscles are recruited for more movements) (Dewald et al. 1995).
Latash and Anson (1996) emphasized that altered motor patterns do not necessarily indicate a failure of the task but, rather, that a CNS reorganization of priorities generates an adaptive change within the redundancy of the motor system. Klatzky (1996) suggested that constraints (e.g., resulting from the motor system or physical environment) result in adjustments of movement priorities. In the reaching task, saturated anterior deltoid activity in individuals with stroke is accompanied by lateral deltoid activity, which results in successful completion of the task (elevating the arm and reaching the target), albeit the interim movement occurs out of the sagittal plane. The significant correlations between shoulder muscle strength and saturation of muscle activity provide further evidence that muscle weakness is one factor that contributes to the necessity of the compensation.
Temporal coupling between the shoulder and elbow was also evident in the paretic arm condition: shoulder abduction with elbow flexion or shoulder internal rotation with elbow extension. These interjoint couplings are consistent with the description of flexor (elbow flexion, shoulder abduction, and external rotation) and extensor (elbow extension, shoulder adduction, and internal rotation) pathological synergies that emerge after stroke (Brunnstrom 1966). The inability to isolate torque generation to selected joints (Dewald and Beer 2001) is consistent with previous observations of abnormal coactivations and interjoint dynamics between the elbow and shoulder joints (Beer et al. 2004; Bourbonnais et al. 1989; Dewald et al. 1995).
A pathological reduction in the number of available synergies may also degrade the ability to execute desired hand trajectories. There were deficits in the quality of hand kinematics in the paretic arm condition, indicating that abnormal joint couplings were detrimental to reaching performance. In both control and stroke subjects (Reisman and Scholz 2003), joint motion errors covary in a compensatory fashion such that the planned hand path is approximately achieved. According to the uncontrolled manifold hypothesis (e.g., Scholz and Schoner 1999), a neural restriction on the number of "goal equivalent postures " (i.e., joint configurations that result in the same hand position) would reduce the effectiveness of this error compensation. Indeed, previous work suggests that neural restrictions are a mechanism that leads to a loss of directional hand control during reaching movements in severe motor impairment (Reinkensmeyer et al. 2002).
The stereotypical reaching strategies of the paretic arm could also result from limited joint range (i.e., contractures) because it has been shown that small reductions in joint ranges can cause large reductions in the number of potential movement synergies that can be performed (Kamper and Rymer 1999). However, participants were excluded from our study if they had significant impairments in the active range of the shoulder and/or elbow and the passive ranges of shoulder and elbow joints were largely unimpaired in these subjects. It is also possible that factors such as comfort or joint pain (Cruse et al. 1990), particularly of the shoulder, could influence the movement planning; however, subjects reported that pain was not present during the test session.
Nonparetic arm has altered joint mechanics
Although there were significant changes to joint motion and mechanical effort (increased abduction angle and flexor-to-abductor power shift) for the nonparetic arm condition, hand motion quality was similar to the control condition. Reduced strength and rate of force generation in the nonparetic upper extremity of individuals with stroke (McCrea et al. 2003) may necessitate alternative recruitment strategies to complete the task. The combined abduction–flexion movement in the nonparetic arm condition likely facilitated a wider recruitment of muscle fibers across the deltoid so that sufficient shoulder power could be developed. The unaltered hand motion quality observed in our study, points to the ability of the CNS to exploit redundancy of the neuromuscular system.
Limitations and conclusions
The reaching distance of the subjects with stroke was determined by the active range of the paretic arm and the mean forward distance was about 85% of the distance that the control subjects used. It is possible that this shorter distance could have promoted a shoulder abductor strategy, although in our pilot testing we never observed a shoulder abductor strategy with the control subjects at short or far reaching distances. It should be noted that, in some cases, the magnitude of muscle activity during reaching movements exceeded 100% of the value obtained during maximum voluntary contractions. This can be attributed to the dependency of EMG amplitude on joint position and velocity (Leedham and Dowling 1995; Nakazawa et al. 1993) (i.e., MVC is isometric, whereas the reaching movement is dynamic). In addition, potentiation may also occur when multiple synergistic muscles are activated during functional movements (De Luca and Erim 2002; Huang and Abraham 2001). Additionally, Landau and Sahrmann (2002) demonstrated that the paretic tibialis anterior muscle of individuals with stroke had lower levels of maximal voluntary torque, but not electrically stimulated force, compared with control subjects, suggesting that the central regulation of muscle activation may be disrupted. Such observations agree with Tang and Rymer (1981) who found that the amount of EMG produced per unit force was greater in the paretic elbow flexor muscles compared with controls and they attributed this increased recruitment from a compensation to the reduced mean motor unit discharge rate that they observed in the paretic muscles. However, others have reported that the EMG–force relationship in the elbow is similar between stroke patients and controls (Fellows et al. 1994). Although individuals with stroke may not be generating a true maximum contraction, the measurement of their "MVC" is important because it provides a relative indication of the available voluntary force with which to undertake functional tasks.
This study examined the differences in reaching characteristics among arm conditions without matching reaching speeds and one may argue that such differences are related to the naturally slower movements of the paretic arm condition. To examine the potential confounding effects of reaching speed, we ran additional analyses of covariance with peak tangential hand velocity (covariate) and found that parameter differences between arm conditions remained significant.
This study shows that movement compensations after stroke are, in part, required to circumvent weakness and saturated muscle activity, which act to restrict the motor abundance of the upper extremity. Strengthening of paretic muscles may potentially limit the lost degrees of freedom and improve the quality of movement compensation. The results of this study can be generalized to individuals with chronic stroke over a broad range of motor impairment (range of score from 13 to 64 out of a possible 66 on the motor component of the upper extremity Fugl-Meyer scale). However, other impairments such as proprioception may also play a role (Mercier et al. 2004) in reaching performance and should be considered separately.
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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Address for reprint requests and other correspondence: J. J. Eng, School of Rehabilitation Sciences, University of British Columbia, T325-2211 Wesbrook Mall, Vancouver, BC, V6T 2B5, Canada (E-mail: Janice.Eng{at}vch.ca)
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