Literature DB >> 22481836

Constraining upper limb synergies of hemiparetic patients using a robotic exoskeleton in the perspective of neuro-rehabilitation.

Vincent Crocher1, Anis Sahbani, Johanna Robertson, Agnès Roby-Brami, Guillaume Morel.   

Abstract

The aim of this paper was to explore how an upper limb exoskeleton can be programmed to impose specific joint coordination patterns during rehabilitation. Based on rationale which emphasizes the importance of the quality of movement coordination in the motor relearning process, a robot controller was developed with the aim of reproducing the individual corrections imposed by a physical therapist on a hemiparetic patient during pointing movements. The approach exploits a description of the joint synergies using principal component analysis (PCA) on joint velocities. This mathematical tool is used both to characterize the patient's movements, with or without the assistance of a physical therapist, and to program the exoskeleton during active-assisted exercises. An original feature of this controller is that the hand trajectory is not imposed on the patient: only the coordination law is modified. Experiments with hemiparetic patients using this new active-assisted mode were conducted. Obtained results demonstrate that the desired inter-joint coordination was successfully enforced, without significantly modifying the trajectory of the end point.

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Year:  2012        PMID: 22481836     DOI: 10.1109/TNSRE.2012.2190522

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  10 in total

1.  Rhythmic affects on stroke-induced joint synergies across a range of speeds.

Authors:  Matt Simkins; Anne Burleigh Jacobs; Jacob Rosen
Journal:  Exp Brain Res       Date:  2013-06-23       Impact factor: 1.972

2.  Dissociating Sensorimotor Recovery and Compensation During Exoskeleton Training Following Stroke.

Authors:  Nadir Nibras; Chang Liu; Denis Mottet; Chunji Wang; David Reinkensmeyer; Olivier Remy-Neris; Isabelle Laffont; Nicolas Schweighofer
Journal:  Front Hum Neurosci       Date:  2021-04-30       Impact factor: 3.169

Review 3.  Robotic exoskeletons: a perspective for the rehabilitation of arm coordination in stroke patients.

Authors:  Nathanaël Jarrassé; Tommaso Proietti; Vincent Crocher; Johanna Robertson; Anis Sahbani; Guillaume Morel; Agnès Roby-Brami
Journal:  Front Hum Neurosci       Date:  2014-12-01       Impact factor: 3.169

4.  Modifying upper-limb inter-joint coordination in healthy subjects by training with a robotic exoskeleton.

Authors:  Tommaso Proietti; Emmanuel Guigon; Agnès Roby-Brami; Nathanaël Jarrassé
Journal:  J Neuroeng Rehabil       Date:  2017-06-12       Impact factor: 4.262

5.  The effects of error-augmentation versus error-reduction paradigms in robotic therapy to enhance upper extremity performance and recovery post-stroke: a systematic review.

Authors:  Le Yu Liu; Youlin Li; Anouk Lamontagne
Journal:  J Neuroeng Rehabil       Date:  2018-07-04       Impact factor: 4.262

6.  Exploiting upper-limb functional principal components for human-like motion generation of anthropomorphic robots.

Authors:  Giuseppe Averta; Cosimo Della Santina; Gaetano Valenza; Antonio Bicchi; Matteo Bianchi
Journal:  J Neuroeng Rehabil       Date:  2020-05-13       Impact factor: 4.262

7.  A framework to describe, analyze and generate interactive motor behaviors.

Authors:  Nathanaël Jarrassé; Themistoklis Charalambous; Etienne Burdet
Journal:  PLoS One       Date:  2012-11-30       Impact factor: 3.240

8.  Neuromotor recovery from stroke: computational models at central, functional, and muscle synergy level.

Authors:  Maura Casadio; Irene Tamagnone; Susanna Summa; Vittorio Sanguineti
Journal:  Front Comput Neurosci       Date:  2013-08-22       Impact factor: 2.380

Review 9.  Assessment of movement quality in robot- assisted upper limb rehabilitation after stroke: a review.

Authors:  Nurdiana Nordin; Sheng Quan Xie; Burkhard Wünsche
Journal:  J Neuroeng Rehabil       Date:  2014-09-12       Impact factor: 4.262

10.  sEMG-Based Motion Recognition of Upper Limb Rehabilitation Using the Improved Yolo-v4 Algorithm.

Authors:  Dongdong Bu; Shuxiang Guo; He Li
Journal:  Life (Basel)       Date:  2022-01-03
  10 in total

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