Literature DB >> 19163633

A clinical evaluation of non-invasive motor imagery-based brain-computer interface in stroke.

Kai Keng Ang1, Cuntai Guan, Karen Sui Geok Chua, Beng Ti Ang, Christopher Wee Keong Kuah, Chuanchu Wang, Kok Soon Phua, Zheng Yang Chin, Haihong Zhang.   

Abstract

This clinical study investigates whether the performance of hemiparetic stroke patients operating a non-invasive Motor Imagery-based Brain-Computer Interface (MI-BCI) is comparable to healthy subjects. The study is performed on 8 healthy subjects and 35 BCI-naïve hemiparetic stroke patients. This study also investigates whether the performance of the stroke patients in operating MI-BCI correlates with the extent of neurological disability. The performance is objectively computed from the 10 x 10-fold cross-validation accuracy of employing the Filter Bank Common Spatial Pattern (FBCSP) algorithm on their EEG measurements. The neurological disability is subjectively estimated using the Fugl-Meyer Assessment (FMA) of the upper extremity. The results show that the performance of BCI-naïve hemiparetic stroke patients is comparable to healthy subjects, and no correlation is found between the accuracy of their performance and their motor impairment in terms of FMA.

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Year:  2008        PMID: 19163633     DOI: 10.1109/IEMBS.2008.4650130

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  4 in total

1.  Single tap identification for fast BCI control.

Authors:  Ian Daly; Slawomir J Nasuto; Kevin Warwick
Journal:  Cogn Neurodyn       Date:  2010-09-01       Impact factor: 5.082

2.  Applying a brain-computer interface to support motor imagery practice in people with stroke for upper limb recovery: a feasibility study.

Authors:  Girijesh Prasad; Pawel Herman; Damien Coyle; Suzanne McDonough; Jacqueline Crosbie
Journal:  J Neuroeng Rehabil       Date:  2010-12-14       Impact factor: 4.262

3.  A Single-Session Preliminary Evaluation of an Affordable BCI-Controlled Arm Exoskeleton and Motor-Proprioception Platform.

Authors:  Ahmed Mohamed Elnady; Xin Zhang; Zhen Gang Xiao; Xinyi Yong; Bubblepreet Kaur Randhawa; Lara Boyd; Carlo Menon
Journal:  Front Hum Neurosci       Date:  2015-03-30       Impact factor: 3.169

4.  Comparison of EEG measurement of upper limb movement in motor imagery training system.

Authors:  Arpa Suwannarat; Setha Pan-Ngum; Pasin Israsena
Journal:  Biomed Eng Online       Date:  2018-08-02       Impact factor: 2.819

  4 in total

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