Dissociating Sensorimotor Recovery and Compensation During Exoskeleton Training Following Stroke
The quality of arm movements typically improves in the sub-acute phase of stroke affecting the upper extremity. Here, we used whole arm kinematic analysis during reaching movements to distinguish whether these improvements are due to true recovery or to compensation. Fifty-three participants with po...
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doaj-566525c4455c4941afb2631f348cf6ec2021-04-30T07:11:26ZengFrontiers Media S.A.Frontiers in Human Neuroscience1662-51612021-04-011510.3389/fnhum.2021.645021645021Dissociating Sensorimotor Recovery and Compensation During Exoskeleton Training Following StrokeNadir Nibras0Chang Liu1Denis Mottet2Chunji Wang3David Reinkensmeyer4Olivier Remy-Neris5Isabelle Laffont6Isabelle Laffont7Nicolas Schweighofer8Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, United StatesDepartment of Biomedical Engineering, University of Southern California, Los Angeles, CA, United StatesEuromov Digital Health in Motion, University of Montpellier, IMT Mines Alès, Montpellier, FranceNeuroscience Graduate Program, University of Southern California, Los Angeles, CA, United StatesDepartment of Mechanical and Aerospace Engineering, Anatomy and Neurobiology, University of California, Irvine, Irvine, CA, United StatesUniversité de Brest, Centre Hospitalier Universitaire, LaTIM-INSERM UMR 1101, Brest, FranceEuromov Digital Health in Motion, University of Montpellier, IMT Mines Alès, Montpellier, FranceMontpellier University Hospital, Euromov Digital Health in Motion, Montpellier University, Montpellier, FranceDivision of Biokinesiology and Physical Therapy, University of Southern California, Los Angeles, CA, United StatesThe quality of arm movements typically improves in the sub-acute phase of stroke affecting the upper extremity. Here, we used whole arm kinematic analysis during reaching movements to distinguish whether these improvements are due to true recovery or to compensation. Fifty-three participants with post-acute stroke performed ∼80 reaching movement tests during 4 weeks of training with the ArmeoSpring exoskeleton. All participants showed improvements in end-effector performance, as measured by movement smoothness. Four ArmeoSpring angles, shoulder horizontal (SH) rotation, shoulder elevation (SE), elbow rotation, and forearm rotation, were recorded and analyzed. We first characterized healthy joint coordination patterns by performing a sparse principal component analysis on these four joint velocities recorded during reaching tests performed by young control participants. We found that two dominant joint correlations [SH with elbow rotation and SE with forearm rotation] explained over 95% of variance of joint velocity data. We identified two clusters of stroke participants by comparing the evolution of these two correlations in all tests. In the “Recoverer” cluster (N = 19), both joint correlations converged toward the respective correlations for control participants. Thus, Recoverers relearned how to generate smooth end-effector movements while developing joint movement patterns similar to those of control participants. In the “Compensator” cluster (N = 34), at least one of the two joint correlations diverged from the corresponding correlation of control participants. Compensators relearned how to generate smooth end-effector movements by discovering various new compensatory movement patterns dissimilar to those of control participants. New compensatory patterns included atypical decoupling of the SE and forearm joints, and atypical coupling of the SH rotation and elbow joints. There was no difference in clinical impairment level between the two groups either at the onset or at the end of training as assessed with the Upper Extremity Fugl-Meyer scale. However, at the start of training, the Recoverers showed significantly faster improvements in end-effector movement smoothness than the Compensators. Our analysis can be used to inform neurorehabilitation clinicians on how to provide movement feedback during practice and suggest avenues for refining exoskeleton robot therapy to reduce compensatory patterns.https://www.frontiersin.org/articles/10.3389/fnhum.2021.645021/fullmotor recoverymotor compensationstrokejoint synergyupper limbneurorehabilitation |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Nadir Nibras Chang Liu Denis Mottet Chunji Wang David Reinkensmeyer Olivier Remy-Neris Isabelle Laffont Isabelle Laffont Nicolas Schweighofer |
spellingShingle |
Nadir Nibras Chang Liu Denis Mottet Chunji Wang David Reinkensmeyer Olivier Remy-Neris Isabelle Laffont Isabelle Laffont Nicolas Schweighofer Dissociating Sensorimotor Recovery and Compensation During Exoskeleton Training Following Stroke Frontiers in Human Neuroscience motor recovery motor compensation stroke joint synergy upper limb neurorehabilitation |
author_facet |
Nadir Nibras Chang Liu Denis Mottet Chunji Wang David Reinkensmeyer Olivier Remy-Neris Isabelle Laffont Isabelle Laffont Nicolas Schweighofer |
author_sort |
Nadir Nibras |
title |
Dissociating Sensorimotor Recovery and Compensation During Exoskeleton Training Following Stroke |
title_short |
Dissociating Sensorimotor Recovery and Compensation During Exoskeleton Training Following Stroke |
title_full |
Dissociating Sensorimotor Recovery and Compensation During Exoskeleton Training Following Stroke |
title_fullStr |
Dissociating Sensorimotor Recovery and Compensation During Exoskeleton Training Following Stroke |
title_full_unstemmed |
Dissociating Sensorimotor Recovery and Compensation During Exoskeleton Training Following Stroke |
title_sort |
dissociating sensorimotor recovery and compensation during exoskeleton training following stroke |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Human Neuroscience |
issn |
1662-5161 |
publishDate |
2021-04-01 |
description |
The quality of arm movements typically improves in the sub-acute phase of stroke affecting the upper extremity. Here, we used whole arm kinematic analysis during reaching movements to distinguish whether these improvements are due to true recovery or to compensation. Fifty-three participants with post-acute stroke performed ∼80 reaching movement tests during 4 weeks of training with the ArmeoSpring exoskeleton. All participants showed improvements in end-effector performance, as measured by movement smoothness. Four ArmeoSpring angles, shoulder horizontal (SH) rotation, shoulder elevation (SE), elbow rotation, and forearm rotation, were recorded and analyzed. We first characterized healthy joint coordination patterns by performing a sparse principal component analysis on these four joint velocities recorded during reaching tests performed by young control participants. We found that two dominant joint correlations [SH with elbow rotation and SE with forearm rotation] explained over 95% of variance of joint velocity data. We identified two clusters of stroke participants by comparing the evolution of these two correlations in all tests. In the “Recoverer” cluster (N = 19), both joint correlations converged toward the respective correlations for control participants. Thus, Recoverers relearned how to generate smooth end-effector movements while developing joint movement patterns similar to those of control participants. In the “Compensator” cluster (N = 34), at least one of the two joint correlations diverged from the corresponding correlation of control participants. Compensators relearned how to generate smooth end-effector movements by discovering various new compensatory movement patterns dissimilar to those of control participants. New compensatory patterns included atypical decoupling of the SE and forearm joints, and atypical coupling of the SH rotation and elbow joints. There was no difference in clinical impairment level between the two groups either at the onset or at the end of training as assessed with the Upper Extremity Fugl-Meyer scale. However, at the start of training, the Recoverers showed significantly faster improvements in end-effector movement smoothness than the Compensators. Our analysis can be used to inform neurorehabilitation clinicians on how to provide movement feedback during practice and suggest avenues for refining exoskeleton robot therapy to reduce compensatory patterns. |
topic |
motor recovery motor compensation stroke joint synergy upper limb neurorehabilitation |
url |
https://www.frontiersin.org/articles/10.3389/fnhum.2021.645021/full |
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