Literature DB >> 32248089

Brain-Computer Interface-Based Soft Robotic Glove Rehabilitation for Stroke.

Nicholas Cheng, Kok Soon Phua, Hwa Sen Lai, Pui Kit Tam, Ka Yin Tang, Kai Kei Cheng, Raye Chen-Hua Yeow, Kai Keng Ang, Cuntai Guan, Jeong Hoon Lim.   

Abstract

OBJECTIVE: This randomized controlled feasibility study investigates the ability for clinical application of the Brain-Computer Interface-based Soft Robotic Glove (BCI-SRG) incorporating activities of daily living (ADL)-oriented tasks for stroke rehabilitation.
METHODS: Eleven recruited chronic stroke patients were randomized into BCI-SRG or Soft Robotic Glove (SRG) group. Each group underwent 120-minute intervention per session comprising 30-minute standard arm therapy and 90-minute experimental therapy (BCI-SRG or SRG). To perform ADL tasks, BCI-SRG group used motor imagery-BCI and SRG, while SRG group used SRG without motor imagery-BCI. Both groups received 18 sessions of intervention over 6 weeks. Fugl-Meyer Motor Assessment (FMA) and Action Research Arm Test (ARAT) scores were measured at baseline (week 0), post- intervention (week 6), and follow-ups (week 12 and 24). In total, 10/11 patients completed the study with 5 in each group and 1 dropped out.
RESULTS: Though there were no significant intergroup differences for FMA and ARAT during 6-week intervention, the improvement of FMA and ARAT seemed to sustain beyond 6-week intervention for BCI-SRG group, as compared with SRG control. Incidentally, all BCI-SRG subjects reported a sense of vivid movement of the stroke-impaired upper limb and 3/5 had this phenomenon persisting beyond intervention while none of SRG did.
CONCLUSION: BCI-SRG suggested probable trends of sustained functional improvements with peculiar kinesthetic experience outlasting active intervention in chronic stroke despite the dire need for large-scale investigations to verify statistical significance. SIGNIFICANCE: Addition of BCI to soft robotic training for ADL-oriented stroke rehabilitation holds promise for sustained improvements as well as elicited perception of motor movements.

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Year:  2020        PMID: 32248089     DOI: 10.1109/TBME.2020.2984003

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  2 in total

1.  The Effect of Brain-Computer Interface Training on Rehabilitation of Upper Limb Dysfunction After Stroke: A Meta-Analysis of Randomized Controlled Trials.

Authors:  Weiwei Yang; Xiaoyun Zhang; Zhenjing Li; Qiongfang Zhang; Chunhua Xue; Yaping Huai
Journal:  Front Neurosci       Date:  2022-02-07       Impact factor: 4.677

2.  Brain-machine interface-based training for improving upper extremity function after stroke: A meta-analysis of randomized controlled trials.

Authors:  Yu-Lei Xie; Yu-Xuan Yang; Hong Jiang; Xing-Yu Duan; Li-Jing Gu; Wu Qing; Bo Zhang; Yin-Xu Wang
Journal:  Front Neurosci       Date:  2022-08-03       Impact factor: 5.152

  2 in total

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