Literature DB >> 28145274

The hybrid BCI system for movement control by combining motor imagery and moving onset visual evoked potential.

Teng Ma1, Hui Li, Lili Deng, Hao Yang, Xulin Lv, Peiyang Li, Fali Li, Rui Zhang, Tiejun Liu, Dezhong Yao, Peng Xu.   

Abstract

OBJECTIVE: Movement control is an important application for EEG-BCI (EEG-based brain-computer interface) systems. A single-modality BCI cannot provide an efficient and natural control strategy, but a hybrid BCI system that combines two or more different tasks can effectively overcome the drawbacks encountered in single-modality BCI control. APPROACH: In the current paper, we developed a new hybrid BCI system by combining MI (motor imagery) and mVEP (motion-onset visual evoked potential), aiming to realize the more efficient 2D movement control of a cursor. MAIN RESULT: The offline analysis demonstrates that the hybrid BCI system proposed in this paper could evoke the desired MI and mVEP signal features simultaneously, and both are very close to those evoked in the single-modality BCI task. Furthermore, the online 2D movement control experiment reveals that the proposed hybrid BCI system could provide more efficient and natural control commands. SIGNIFICANCE: The proposed hybrid BCI system is compensative to realize efficient 2D movement control for a practical online system, especially for those situations in which P300 stimuli are not suitable to be applied.

Mesh:

Year:  2017        PMID: 28145274     DOI: 10.1088/1741-2552/aa5d5f

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


  14 in total

1.  Novel hybrid brain-computer interface system based on motor imagery and P300.

Authors:  Cili Zuo; Jing Jin; Erwei Yin; Rami Saab; Yangyang Miao; Xingyu Wang; Dewen Hu; Andrzej Cichocki
Journal:  Cogn Neurodyn       Date:  2019-10-21       Impact factor: 5.082

2.  A multi-modal brain-computer interface based on threshold discrimination and its application in wheelchair control.

Authors:  Enzeng Dong; Haoran Zhang; Lin Zhu; Shengzhi Du; Jigang Tong
Journal:  Cogn Neurodyn       Date:  2022-01-24       Impact factor: 3.473

Review 3.  Hybrid Brain-Computer Interface Techniques for Improved Classification Accuracy and Increased Number of Commands: A Review.

Authors:  Keum-Shik Hong; Muhammad Jawad Khan
Journal:  Front Neurorobot       Date:  2017-07-24       Impact factor: 2.650

Review 4.  A systematic review of hybrid brain-computer interfaces: Taxonomy and usability perspectives.

Authors:  Inchul Choi; Ilsun Rhiu; Yushin Lee; Myung Hwan Yun; Chang S Nam
Journal:  PLoS One       Date:  2017-04-28       Impact factor: 3.240

5.  Frequency Specific Cortical Dynamics During Motor Imagery Are Influenced by Prior Physical Activity.

Authors:  Selina C Wriessnegger; Clemens Brunner; Gernot R Müller-Putz
Journal:  Front Psychol       Date:  2018-10-25

6.  A Decoding Scheme for Incomplete Motor Imagery EEG With Deep Belief Network.

Authors:  Yaqi Chu; Xingang Zhao; Yijun Zou; Weiliang Xu; Jianda Han; Yiwen Zhao
Journal:  Front Neurosci       Date:  2018-09-28       Impact factor: 4.677

Review 7.  Summary of over Fifty Years with Brain-Computer Interfaces-A Review.

Authors:  Aleksandra Kawala-Sterniuk; Natalia Browarska; Amir Al-Bakri; Mariusz Pelc; Jaroslaw Zygarlicki; Michaela Sidikova; Radek Martinek; Edward Jacek Gorzelanczyk
Journal:  Brain Sci       Date:  2021-01-03

8.  Using Coherence-based spectro-spatial filters for stimulus features prediction from electro-corticographic recordings.

Authors:  Jaime Delgado Saa; Andy Christen; Stephanie Martin; Brian N Pasley; Robert T Knight; Anne-Lise Giraud
Journal:  Sci Rep       Date:  2020-05-06       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.  Optimization of Task Allocation for Collaborative Brain-Computer Interface Based on Motor Imagery.

Authors:  Bin Gu; Minpeng Xu; Lichao Xu; Long Chen; Yufeng Ke; Kun Wang; Jiabei Tang; Dong Ming
Journal:  Front Neurosci       Date:  2021-07-02       Impact factor: 4.677

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