Literature DB >> 31180829

Assessment of the Efficacy of EEG-Based MI-BCI With Visual Feedback and EEG Correlates of Mental Fatigue for Upper-Limb Stroke Rehabilitation.

Ruyi Foong, Kai Keng Ang, Chai Quek, Cuntai Guan, Kok Soon Phua, Christopher Wee Keong Kuah, Vishwanath Arun Deshmukh, Lester Hon Lum Yam, Deshan Kumar Rajeswaran, Ning Tang, Effie Chew, Karen Sui Geok Chua.   

Abstract

OBJECTIVE: This single-arm multisite trial investigates the efficacy of the neurostyle brain exercise therapy towards enhanced recovery (nBETTER) system, an electroencephalogram (EEG)-based motor imagery brain-computer interface (MI-BCI) employing visual feedback for upper-limb stroke rehabilitation, and the presence of EEG correlates of mental fatigue during BCI usage.
METHODS: A total of 13 recruited stroke patients underwent thrice-weekly nBETTER therapy coupled with standard arm therapy over six weeks. Upper-extremity Fugl-Meyer motor assessment (FMA) scores were measured at baseline (week 0), post-intervention (week 6), and follow-ups (weeks 12 and 24). In total, 11/13 patients (mean age 55.2 years old, mean post-stroke duration 333.7 days, mean baseline FMA 35.5) completed the study.
RESULTS: Significant FMA gains relative to baseline were observed at weeks 6 and 24. Retrospectively comparing to the standard arm therapy (SAT) control group and BCI with haptic knob (BCI-HK) intervention group from a previous similar study, the SAT group had no significant gains, whereas the BCI-HK group had significant gains at weeks 6, 12, and 24. EEG analysis revealed significant positive correlations between relative beta power and BCI performance in the frontal and central brain regions, suggesting that mental fatigue may contribute to poorer BCI performance.
CONCLUSION: nBETTER, an EEG-based MI-BCI employing only visual feedback, helps stroke survivors sustain short-term FMA improvement. Analysis of EEG relative beta power indicates that mental fatigue may be present. SIGNIFICANCE: This study adds nBETTER to the growing literature of safe and effective stroke rehabilitation MI-BCI, and suggests an additional fatigue-monitoring role in future such BCI.

Entities:  

Year:  2019        PMID: 31180829     DOI: 10.1109/TBME.2019.2921198

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


  17 in total

1.  Relative Power Correlates With the Decoding Performance of Motor Imagery Both Across Time and Subjects.

Authors:  Qing Zhou; Jiafan Lin; Lin Yao; Yueming Wang; Yan Han; Kedi Xu
Journal:  Front Hum Neurosci       Date:  2021-08-13       Impact factor: 3.473

2.  BCI-Based Rehabilitation on the Stroke in Sequela Stage.

Authors:  Yangyang Miao; Shugeng Chen; Xinru Zhang; Jing Jin; Ren Xu; Ian Daly; Jie Jia; Xingyu Wang; Andrzej Cichocki; Tzyy-Ping Jung
Journal:  Neural Plast       Date:  2020-12-13       Impact factor: 3.599

3.  An Inter- and Intra-Subject Transfer Calibration Scheme for Improving Feedback Performance of Sensorimotor Rhythm-Based BCI Rehabilitation.

Authors:  Lei Cao; Shugeng Chen; Jie Jia; Chunjiang Fan; Haoran Wang; Zhixiong Xu
Journal:  Front Neurosci       Date:  2021-01-28       Impact factor: 4.677

4.  The Application of Technological Intervention for Stroke Rehabilitation in Southeast Asia: A Scoping Review With Stakeholders' Consultation.

Authors:  Siti Nur Suhaidah Selamat; Rosalam Che Me; Husna Ahmad Ainuddin; Mazatulfazura S F Salim; Hafiz Rashidi Ramli; Muhammad Hibatullah Romli
Journal:  Front Public Health       Date:  2022-02-07

Review 5.  Poststroke Cognitive Impairment Research Progress on Application of Brain-Computer Interface.

Authors:  Xiaowei Sun; Mingyue Li; Quan Li; Hongna Yin; Xicheng Jiang; Hongtao Li; Zhongren Sun; Tiansong Yang
Journal:  Biomed Res Int       Date:  2022-02-07       Impact factor: 3.411

6.  EEG Spectral Feature Modulations Associated With Fatigue in Robot-Mediated Upper Limb Gross and Fine Motor Interactions.

Authors:  Udeshika C Dissanayake; Volker Steuber; Farshid Amirabdollahian
Journal:  Front Neurorobot       Date:  2022-01-20       Impact factor: 2.650

7.  Sensorimotor Rhythm-Brain Computer Interface With Audio-Cue, Motor Observation and Multisensory Feedback for Upper-Limb Stroke Rehabilitation: A Controlled Study.

Authors:  Xin Li; Lu Wang; Si Miao; Zan Yue; Zhiming Tang; Liujie Su; Yadan Zheng; Xiangzhen Wu; Shan Wang; Jing Wang; Zulin Dou
Journal:  Front Neurosci       Date:  2022-03-11       Impact factor: 4.677

8.  Handedness effects on motor imagery during kinesthetic and visual-motor conditions.

Authors:  Dariusz Zapała; Paulina Iwanowicz; Piotr Francuz; Paweł Augustynowicz
Journal:  Sci Rep       Date:  2021-06-23       Impact factor: 4.379

9.  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

10.  Brain Functional Changes in Stroke Following Rehabilitation Using Brain-Computer Interface-Assisted Motor Imagery With and Without tDCS: A Pilot Study.

Authors:  Mengjiao Hu; Hsiao-Ju Cheng; Fang Ji; Joanna Su Xian Chong; Zhongkang Lu; Weimin Huang; Kai Keng Ang; Kok Soon Phua; Kai-Hsiang Chuang; Xudong Jiang; Effie Chew; Cuntai Guan; Juan Helen Zhou
Journal:  Front Hum Neurosci       Date:  2021-07-16       Impact factor: 3.169

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