Literature DB >> 28607219

Transcranial direct current stimulation versus user training on improving online myoelectric control for amputees.

Lizhi Pan1, Dingguo Zhang, Ning Jiang, Xinjun Sheng, Xiangyang Zhu.   

Abstract

OBJECTIVE: Transcranial direct current stimulation (tDCS) and user training (UT) are two types of methods to improve myoelectric control performance for amputees. In this study, we compared the independent effect between tDCS and UT, and investigated the combined effect of tDCS and UT. APPROACH: An online paradigm of simultaneous and proportional control (SPC) based on electromyography (EMG) was adopted. The proposed experiments were conducted on six naïve unilateral trans-radial amputees. The subjects each received three types of 20 min interventions: active tDCS with motor training (tDCS  +  UT), active tDCS with quiet sitting (tDCS), and sham tDCS with motor training (UT). The interventions were applied at one week intervals in a randomized order. The subjects performed online control of a feedback arrow with two degrees of freedom (DoFs) to accomplish target reaching motor tasks in pre-sessions and post-sessions. We compared the performance, measured by completion rate, completion time, and efficiency coefficient, between pre-sessions and post-sessions. MAIN
RESULTS: The results showed that the intervention tDCS  +  UT and tDCS significantly improved the online SPC performance (i.e. improved the completion rate; reduced the completion time; and improved the efficiency coefficient), while intervention UT did not significantly change the performance. The results also showed that the online SPC performance after intervention tDCS  +  UT and tDCS was not significantly different, but both were significantly better than that after intervention UT. SIGNIFICANCE: tDCS could be an effective intervention to improve the online SPC performance in a short time.

Mesh:

Year:  2017        PMID: 28607219     DOI: 10.1088/1741-2552/aa758e

Source DB:  PubMed          Journal:  J Neural Eng        ISSN: 1741-2552            Impact factor:   5.379


  1 in total

1.  sEMG-Based Drawing Trace Reconstruction: A Novel Hybrid Algorithm Fusing Gene Expression Programming into Kalman Filter.

Authors:  Zhongliang Yang; Yangliang Wen; Yumiao Chen
Journal:  Sensors (Basel)       Date:  2018-09-30       Impact factor: 3.576

  1 in total

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