The Continuity of Movements

Brooks, V. B.; Cooke, J. D.; Thomas, Justin M.

doi:10.1007/978-1-4613-4547-3_22

Cited by 56 publications

(26 citation statements)

References 10 publications

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“…We calculated robot-based metrics from kinematic data recorded by the robot during pre-post training unassisted trials and the unassisted trial at the 48-hour retest [27][28][29]; each trial consisted of 40 point-to-point movements.…”

Section: Discussionmentioning

confidence: 99%

“…The selection of our motor control measures was based in part on performance indices used and validated in studies for arm reaching investigating ML in human subjects within a virtual mechanical environment generated by a perturbation force field [24][25][26][31][32][33]. For example, normalized jerk and peak and mean speed have been used to quantify motor performance in nondisabled and neurologically impaired individuals [27][28][29]34]. However, unlike this study, none of those studies …”

Section: Paradigm and Motor Control Metricsmentioning

confidence: 99%

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Short-term ankle motor performance with ankle robotics training in chronic hemiparetic stroke

Anindo¹,

Forrester²,

Macko³

2011

JRRD

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Abstract-Cerebrovascular accident (stroke) often results in impaired motor control and persistent weakness that may lead to chronic disability, including deficits in gait and balance function. Finding ways to restore motor control may help reduce these deficits; however, little is known regarding the capacity or temporal profile of short-term motor adaptations and learning at the hemiparetic ankle. Our objective was to determine the shortterm effects of a single session of impedance-controlled ankle robot ("anklebot") training on paretic ankle motor control in chronic stroke. This was a double-arm pilot study on a convenience sample of participants with chronic stroke (n = 7) who had residual hemiparetic deficits and an equal number of ageand sex-matched nondisabled control subjects. Training consisted of participants in each group playing a target-based video game with the anklebot for an hour, for a total of 560 movement repetitions in dorsiflexion/plantar flexion ranges followed by retest 48 hours later. Task difficulty was adjusted to ankle range of motion, with robotic assistance decreased incrementally across training. Assessments included robotic measures of ankle motor control on unassisted trials before and after training and at 48 hours after training. Following exposure to the task, subjects with stroke improved paretic ankle motor control across a single training session as indexed by increased targeting accuracy (21.6 +/-8.0 to 31.4 +/-4.8, p = 0.05), higher angular speeds (mean: 4.7 +/-1.5 degrees/s to 6.5 +/-2.6 degrees/s, p < 0.01, peak: 42.8 +/-9.0 degrees/s to 45.6 +/-9.4 degrees/s, p = 0.03), and smoother movements (normalized jerk: 654.1 +/-103.3 s -2 to 537.6 +/-86.7 s -2 , p < 0.005, number of speed peaks: 27.1 +/ -5.8 to 23.7 +/-4.1, p < 0.01). In contrast, nondisabled subjects did not make statistically significant gains in any metric after training except in the number of successful passages (32.3 +/-7.5 to 36.5 +/-6.4, p = 0.006). Gains in all five motor control metrics were retained (p > 0.05) at 48 hours in both groups. Robust maintenance of motor adaptation in the robot-trained paretic ankle over 48 hours may be indicative of short-term motor learning. Our initial results suggest that the anklebot may be a flexible motor learning platform with the potential to detect rapid changes in ankle motor performance poststroke.Key words: ankle motor control, ankle robot, hemiparesis, jerk, learning rate, motor adaptation, motor learning, movement smoothness, neurorehabilitation, stroke.Abbreviations: AL = associative motor learning; AROM = active range of motion; CL = cognitive learning; DF = dorsiflexion; DOF = degree of freedom; GRECC = Geriatric Research, Education, and Clinical Center; HP = hemiparetic; INV/EV = inversion-eversion; LL = lower limb; MA = motor adaptation; MAS = Modified Ashworth Scale; ML = motor learning; MMT = Manual Muscle Test; NIHSS = National Institutes of Health Stroke Scale; PF = plantar flexion; ROM = range of motion; STMA = short-term motor adaptation; STML = sho...

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Section: Discussionmentioning

confidence: 99%

Section: Paradigm and Motor Control Metricsmentioning

confidence: 99%

Short-term ankle motor performance with ankle robotics training in chronic hemiparetic stroke

Anindo¹,

Forrester²,

Macko³

2011

JRRD

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“…The number of peaks in a speed profile has been used to quantif y smoothness in healthy subjects (Brooks et al, 1973;Fetters and Todd, 1987) and in stroke patients (Kahn et al, 2001). Fewer peaks in speed represent fewer periods of acceleration and deceleration, making a smoother movement.…”

Section: Methodsmentioning

confidence: 99%

“…Smoothness measures have most often been based on minimizing jerk, the third time derivative of position (Flash and Hogan, 1985), although many other measures are possible, including snap, the fourth time derivative of position (Edelman and Flash, 1987), and counting peaks in speed (Brooks et al, 1973;Fetters and Todd, 1987;Cirstea and Levin, 2000;Kahn et al, 2001). Smoothness in the minimum-jerk sense has been used to identify presymptomatic individuals with Huntington's disease (Smith et al, 2000) and has also been shown to account for the two-thirds power law, widely considered an invariant in human movement (Wann et al, 1988;Gribble and Ostry, 1996;Todorov and Jordan, 1998;Schaal and Sternad, 2001).…”

mentioning

confidence: 99%

Movement Smoothness Changes during Stroke Recovery

Rohrer¹,

Fasoli²,

Krebs³

et al. 2002

J. Neurosci.

659

610

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Smoothness is characteristic of coordinated human movements, and stroke patients' movements seem to grow more smooth with recovery. We used a robotic therapy device to analyze five different measures of movement smoothness in the hemiparetic arm of 31 patients recovering from stroke. Four of the five metrics showed general increases in smoothness for the entire patient population. However, according to the fifth metric, the movements of patients with recent stroke grew less smooth over the course of therapy. This pattern was reproduced in a computer simulation of recovery based on submovement blending, suggesting that progressive blending of submovements underlies stroke recovery.

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“…Single-peaked velocity profiles were rare in the present study because our paradigm allowed enough time for movements of moderate speed (with several acceleration zero crossings, Brooks et al 1973;Polit and Bizzi 1979). Only overtrained subjects made consistent use of fast, single-peaked movements (Fig.…”

Section: Optimal Tactical Composition Of Movementsmentioning

confidence: 67%

Learning "what" and "how" in a human motor task.

Brooks¹,

Hilperath²,

Brooks³

et al. 1995

Learn. Mem.

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We studied the development of implicit and of verbally declared knowledge for normal human subjects who learned an unfamiliar motor task in one learning session. The exploratory nature of motor learning and a special period for optimizing skill were followed in real time. Subjects understood the goal for task success, but they had to learn a motor strategy of what pattern of serial movements to make and the tactics of bow much to scale their amplitudes and timing. We compared the time course for acquiring tactical skill with that for acquiring knowledge of strategy and of tactics, and their necessary cues. Implicit and declarative knowledge were distinguished from one another by correlating subjects' verbal self-reports with movement kinematics and their results. Implicit generation of the correct strategy and of the tactics developed in an exploratory manner from the beginning of the learning session. Implicit strategy learning soon gave way to conscious efforts, but tactical learn.ing remained implicit until its first unambiguous verbal declaration 5Corresponding author.(with one exception). First strategy declarations were voiced before those for tactics, during trial-and-error learning that did not require task success, and referred to reversing the direction of hand movements (one exception). In contrast, first declarations of tactics almost always required actual or imminent success, referred to when direction was to be reversed, and it was achieved near the top of a sigmoid learning curve that rose to tactical skill (with one exception). During the sigmoid rise, movement amplitudes and timing were optimized in a distinct manner, although tactics usually adapted thereafter to movements of more moderate speed that could still be successful.

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The Continuity of Movements

Cited by 56 publications

References 10 publications

Short-term ankle motor performance with ankle robotics training in chronic hemiparetic stroke

Short-term ankle motor performance with ankle robotics training in chronic hemiparetic stroke

Movement Smoothness Changes during Stroke Recovery

Learning "what" and "how" in a human motor task.

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