Augmented Dynamics and Motor Exploration as Training for Stroke

Huang, Felix C.; Patton, James L.

doi:10.1109/tbme.2012.2192116

Cited by 41 publications

(42 citation statements)

References 36 publications

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“…This finding is consistent with the observation (Wu et al, 2014) that greater variability—and therefore a greater amount of exploration—leads to more accurate adaptation to unfamiliar dynamics. Our results are also consistent with previous observations that training within negative viscous fields has a facilitatory effect on sensorimotor adaptation (Huang et al, 2010) and neuromotor recovery from stroke (Huang and Patton, 2011, 2013). …”

Section: Discussionsupporting

confidence: 93%

Effect of Position- and Velocity-Dependent Forces on Reaching Movements at Different Speeds

Summa

Casadio

Sanguineti

2016

Front. Hum. Neurosci.

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The speed of voluntary movements is determined by the conflicting needs of maximizing accuracy and minimizing mechanical effort. Dynamic perturbations, e.g., force fields, may be used to manipulate movements in order to investigate these mechanisms. Here, we focus on how the presence of position- and velocity-dependent force fields affects the relation between speed and accuracy during hand reaching movements. Participants were instructed to perform reaching movements under visual control in two directions, corresponding to either low or high arm inertia. The subjects were required to maintain four different movement durations (very slow, slow, fast, very fast). The experimental protocol included three phases: (i) familiarization—the robot generated no force; (ii) force field—the robot generated a force; and (iii) after-effect—again, no force. Participants were randomly assigned to four groups, depending on the type of force that was applied during the “force field” phase. The robot was programmed to generate position-dependent forces—with positive (K+) or negative stiffness (K−)—or velocity-dependent forces, with either positive (B+) or negative viscosity (B−). We focused on path curvature, smoothness, and endpoint error; in the latter we distinguished between bias and variability components. Movements in the high-inertia direction are smoother and less curved; smoothness also increases with movement speed. Endpoint bias and variability are greater in, respectively, the high and low inertia directions. A robust dependence on movement speed was only observed in the longitudinal components of both bias and variability. The strongest and more consistent effects of perturbation were observed with negative viscosity (B−), which resulted in increased variability during force field adaptation and in a reduction of the endpoint bias, which was retained in the subsequent after-effect phase. These findings confirm that training with negative viscosity produces lasting effects in movement accuracy at all speeds.

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Section: Discussionsupporting

confidence: 93%

Effect of Position- and Velocity-Dependent Forces on Reaching Movements at Different Speeds

Summa

Casadio

Sanguineti

2016

Front. Hum. Neurosci.

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“…In pilot studies, however, one participant's unassisted reachable workspace appeared to increase immediately after a short period of exercise with exomuscle support when compared to unassisted reachable workspace before the exercise. Such session effects are rarely reported [37], [38] and the neurophysiological mechanisms for such spontaneous recovery, if they exist, could be useful to investigate. We thus designed a protocol to not only assess (1) reachable workspace and (2) flexor synergy activation in each support condition, but also (3) whether a short period of assisted exercise could produce short-term motor improvements.…”

Section: A Methodsmentioning

confidence: 99%

Upper extremity exomuscle for shoulder abduction support

Simpson

Huerta

Sketch

et al. 2020

Preprint

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Assistive devices may aid motor recovery after a stroke, but access to such devices is limited. Exosuits may be a more accessible alternative to current devices and have been used to successfully assist movement after a variety of motor impairments, but we know little about how they might assist post-stroke upper extremity movement. Here, we designed an exosuit actuator to support shoulder abduction, which we call an "exomuscle" and is based on a form of growing robot known as a pneumatic-reel actuator. We also assembled a ceiling-mounted support to serve as a positive control. We verified that both supports reduce the activity of shoulder abductor muscles and do not impede range of motion in healthy participants (n=4). Then, we measured reachable workspace area in stroke survivors (n=6) both with and without support. Our exomuscle increased workspace area in four participants (180±90 cm 2 ) while the ceiling support increased workspace area in five participants (792±540 cm 2 ). Design decisions that make the exomuscle wearable, such as leaving the forearm free, likely contribute to the performance differences between the two supports. Heterogeneity amongst stroke survivors' abilities likely contribute to a high variability in our results. Though both supports resulted in similar performance for healthy participants, the performance differences in stroke survivors highlight the need to validate assistive devices in the target population.

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“…Researchers have computed work and power to characterize normal and abnormal gait patterns [10,11], to evaluate robotassisted locomotion [12], and to reduce energetic costs when using exoskeletons [13]. Recently our work has focused on robotic augmentation of upper limb dynamics to facilitate vigorous movement during practice [14,15]. We showed that stroke survivors increase total work output during force training [16].…”

Section: Introductionmentioning

confidence: 95%

Key components of mechanical work predict outcomes in robotic stroke therapy

Wright

Majeed

Patton

et al. 2020

J NeuroEngineering Rehabil

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Background: Clinical practice typically emphasizes active involvement during therapy. However, traditional approaches can offer only general guidance on the form of involvement that would be most helpful to recovery. Beyond assisting movement, robots allow comprehensive methods for measuring practice behaviors, including the energetic input of the learner. Using data from our previous study of robot-assisted therapy, we examined how separate components of mechanical work contribute to predicting training outcomes. Methods: Stroke survivors (n = 11) completed six sessions in two-weeks of upper extremity motor exploration (selfdirected movement practice) training with customized forces, while a control group (n = 11) trained without assistance. We employed multiple regression analysis to predict patient outcomes with computed mechanical work as independent variables, including separate features for elbow versus shoulder joints, positive (concentric) and negative (eccentric), flexion and extension. Results: Our analysis showed that increases in total mechanical work during therapy were positively correlated with our final outcome metric, velocity range. Further analysis revealed that greater amounts of negative work at the shoulder and positive work at the elbow as the most important predictors of recovery (using cross-validated regression, R 2 = 52%). However, the work features were likely mutually correlated, suggesting a prediction model that first removed shared variance (using PCA, R 2 = 65-85%). Conclusions: These results support robotic training for stroke survivors that increases energetic activity in eccentric shoulder and concentric elbow actions.

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Augmented Dynamics and Motor Exploration as Training for Stroke

Cited by 41 publications

References 36 publications

Effect of Position- and Velocity-Dependent Forces on Reaching Movements at Different Speeds

Effect of Position- and Velocity-Dependent Forces on Reaching Movements at Different Speeds

Upper extremity exomuscle for shoulder abduction support

Key components of mechanical work predict outcomes in robotic stroke therapy

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