Literature DB >> 30442610

An Asynchronous Control Paradigm Based on Sequential Motor Imagery and Its Application in Wheelchair Navigation.

Yang Yu, Yadong Liu, Jun Jiang, Erwei Yin, Zongtan Zhou, Dewen Hu.   

Abstract

In this paper, an asynchronous control paradigm based on sequential motor imagery (sMI) is proposed to enrich the control commands of a motor imagery -based brain-computer interface. We test the feasibility and report the performance of this paradigm in wheelchair navigation control. By sequentially imaging left- and right-hand movements, the subjects can complete four sMI tasks in an asynchronous mode that are then encoded to control six steering functions of a wheelchair, including moving forward, turning left, turning right, accelerating, decelerating, and stopping. Two experiments, a simulated experiment, and an online wheelchair navigation experiment, were conducted to evaluate the performance of the proposed approach in seven subjects. In summary, the subjects completed 99 of 105 experimental trials along a predefined route. The success rate was 94.2% indicating the practicality and the effectiveness of the proposed asynchronous control paradigm in wheelchair navigation control.

Mesh:

Year:  2018        PMID: 30442610     DOI: 10.1109/TNSRE.2018.2881215

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  6 in total

Review 1.  Progress in Brain Computer Interface: Challenges and Opportunities.

Authors:  Simanto Saha; Khondaker A Mamun; Khawza Ahmed; Raqibul Mostafa; Ganesh R Naik; Sam Darvishi; Ahsan H Khandoker; Mathias Baumert
Journal:  Front Syst Neurosci       Date:  2021-02-25

2.  Decentralized Motion Control for Omnidirectional Wheelchair Tracking Error Elimination Using PD-Fuzzy-P and GA-PID Controllers.

Authors:  Wafa Batayneh; Yusra AbuRmaileh
Journal:  Sensors (Basel)       Date:  2020-06-22       Impact factor: 3.576

3.  A novel brain-controlled wheelchair combined with computer vision and augmented reality.

Authors:  Kaixuan Liu; Yang Yu; Yadong Liu; Jingsheng Tang; Xinbin Liang; Xingxing Chu; Zongtan Zhou
Journal:  Biomed Eng Online       Date:  2022-07-26       Impact factor: 3.903

Review 4.  A Comprehensive Review of Endogenous EEG-Based BCIs for Dynamic Device Control.

Authors:  Natasha Padfield; Kenneth Camilleri; Tracey Camilleri; Simon Fabri; Marvin Bugeja
Journal:  Sensors (Basel)       Date:  2022-08-03       Impact factor: 3.847

Review 5.  A Comprehensive Review on Critical Issues and Possible Solutions of Motor Imagery Based Electroencephalography Brain-Computer Interface.

Authors:  Amardeep Singh; Ali Abdul Hussain; Sunil Lal; Hans W Guesgen
Journal:  Sensors (Basel)       Date:  2021-03-20       Impact factor: 3.576

6.  A Two-Branch CNN Fusing Temporal and Frequency Features for Motor Imagery EEG Decoding.

Authors:  Jun Yang; Siheng Gao; Tao Shen
Journal:  Entropy (Basel)       Date:  2022-03-08       Impact factor: 2.524

  6 in total

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