Literature DB >> 26876690

Effects of Brain-Computer Interface-controlled Functional Electrical Stimulation Training on Shoulder Subluxation for Patients with Stroke: A Randomized Controlled Trial.

Yun Young Jang1, Tae Hoon Kim1,2, Byoung Hee Lee1.   

Abstract

The purpose of this study was to investigate the effects of brain-computer interface (BCI)-controlled functional electrical stimulation (FES) training on shoulder subluxation of patients with stroke. Twenty subjects were randomly divided into two groups: the BCI-FES group (n = 10) and the FES group (n = 10). Patients in the BCI-FES group were administered conventional therapy with the BCI-FES on the shoulder subluxation area of the paretic upper extremity, five times per week during 6 weeks, while the FES group received conventional therapy with FES only. All patients were assessed for shoulder subluxation (vertical distance, VD; horizontal distance, HD), pain (visual analogue scale, VAS) and the Manual Function Test (MFT) at the time of recruitment to the study and after 6 weeks of the intervention. The BCI-FES group demonstrated significant improvements in VD, HD, VAS and MFT after the intervention period, while the FES group demonstrated significant improvements in HD, VAS and MFT. There were also significant differences in the VD and two items (shoulder flexion and abduction) of the MFT between the two groups. The results of this study suggest that BCI-FES training may be effective in improving shoulder subluxation of patients with stroke by facilitating motor recovery.
Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Entities:  

Keywords:  brain-computer interface; rehabilitation; shoulder subluxation; stroke

Mesh:

Year:  2016        PMID: 26876690     DOI: 10.1002/oti.1422

Source DB:  PubMed          Journal:  Occup Ther Int        ISSN: 0966-7903            Impact factor:   1.448


  16 in total

1.  BCI-FES With Multimodal Feedback for Motor Recovery Poststroke.

Authors:  Alexander B Remsik; Peter L E van Kan; Shawna Gloe; Klevest Gjini; Leroy Williams; Veena Nair; Kristin Caldera; Justin C Williams; Vivek Prabhakaran
Journal:  Front Hum Neurosci       Date:  2022-07-06       Impact factor: 3.473

2.  EEG-controlled functional electrical stimulation rehabilitation for chronic stroke: system design and clinical application.

Authors:  Long Chen; Bin Gu; Zhongpeng Wang; Lei Zhang; Minpeng Xu; Shuang Liu; Feng He; Dong Ming
Journal:  Front Med       Date:  2021-06-22       Impact factor: 4.592

3.  Generalizability of Results from Randomized Controlled Trials in Post-Stroke Physiotherapy.

Authors:  Matteo Paci; Claudia Prestera; Francesco Ferrarello
Journal:  Physiother Can       Date:  2020-11-01       Impact factor: 1.037

Review 4.  Neurotechnology-aided interventions for upper limb motor rehabilitation in severe chronic stroke.

Authors:  Martina Coscia; Maximilian J Wessel; Ujwal Chaudary; José Del R Millán; Silvestro Micera; Adrian Guggisberg; Philippe Vuadens; John Donoghue; Niels Birbaumer; Friedhelm C Hummel
Journal:  Brain       Date:  2019-08-01       Impact factor: 13.501

5.  Therapeutic effects of brain-computer interface-controlled functional electrical stimulation training on balance and gait performance for stroke: A pilot randomized controlled trial.

Authors:  Eunjung Chung; Byoung-Hee Lee; Sujin Hwang
Journal:  Medicine (Baltimore)       Date:  2020-12-18       Impact factor: 1.817

6.  Protocols Used by Occupational Therapists on Shoulder Pain after Stroke: Systematic Review and Meta-Analysis.

Authors:  Isis Gabriele De Souza; Raphael Fabricio De Souza; Felipe Douglas Silva Barbosa; Kelly Regina Dias Da Silva Scipioni; Felipe J Aidar; Aristela De Freitas Zanona
Journal:  Occup Ther Int       Date:  2021-05-03       Impact factor: 1.448

7.  The effect of visual and proprioceptive feedback on sensorimotor rhythms during BCI training.

Authors:  Hanna-Leena Halme; Lauri Parkkonen
Journal:  PLoS One       Date:  2022-02-23       Impact factor: 3.240

8.  Artificial neural network EMG classifier for functional hand grasp movements prediction.

Authors:  Marta Gandolla; Simona Ferrante; Giancarlo Ferrigno; Davide Baldassini; Franco Molteni; Eleonora Guanziroli; Michele Cotti Cottini; Carlo Seneci; Alessandra Pedrocchi
Journal:  J Int Med Res       Date:  2016-09-27       Impact factor: 1.671

Review 9.  Brain-computer interfaces for post-stroke motor rehabilitation: a meta-analysis.

Authors:  María A Cervera; Surjo R Soekadar; Junichi Ushiba; José Del R Millán; Meigen Liu; Niels Birbaumer; Gangadhar Garipelli
Journal:  Ann Clin Transl Neurol       Date:  2018-03-25       Impact factor: 4.511

10.  Immediate and long-term effects of BCI-based rehabilitation of the upper extremity after stroke: a systematic review and meta-analysis.

Authors:  Zhongfei Bai; Kenneth N K Fong; Jack Jiaqi Zhang; Josephine Chan; K H Ting
Journal:  J Neuroeng Rehabil       Date:  2020-04-25       Impact factor: 4.262

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