Performance Evaluation of Walking Imagery Training Based on Virtual Environment in Brain-Computer Interfaces

Xiaolu Liu; Shuang Liang; Wenlong Hang; Baiying Lei; Qiong Wang; Jing Qin; Kup Sze Choi

doi:10.1109/ISM.2017.15

Performance Evaluation of Walking Imagery Training Based on Virtual Environment in Brain-Computer Interfaces

Xiaolu Liu, Shuang Liang, Wenlong Hang, Baiying Lei, Qiong Wang, Jing Qin, Kup Sze Choi

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

5 Citations (Scopus)

Abstract

Motor imagery (MI) based on brain computer interfaces (BCIs) have been widely applied for upper limb motor rehabilitation. Due to the fact that a large number of disabled people need to restore or improve walking ability, it is also important to investigate the use of MI-based BCIs for lower limb motor rehabilitation. The brain activity of lower limb MI is more difficult to detect because of low reliability. The purpose of this study is to find a suitable paradigm of walking imagery to achieve better training effect and ensure reliable brain activity. We developed the text-based paradigm and the virtual environment (VE)-based paradigm, and evaluated their performance on identifying walking imagery from idle state.The experimental results provide evidences that the VE-based paradigm could improve the average classification accuracy. This paradigm would induce EEG patterns that make them easier for single-trial detection of walking imagery. This study has the potential to improve the reliability and robustness of walking imagery based BCIs.

Original language	English
Title of host publication	Proceedings - 2017 IEEE International Symposium on Multimedia, ISM 2017
Publisher	IEEE
Pages	25-30
Number of pages	6
Volume	2017-January
ISBN (Electronic)	9781538629369
DOIs	https://doi.org/10.1109/ISM.2017.15
Publication status	Published - 28 Dec 2017
Event	19th IEEE International Symposium on Multimedia, ISM 2017 - Taichung, Taiwan Duration: 11 Dec 2017 → 13 Dec 2017

Conference

Conference	19th IEEE International Symposium on Multimedia, ISM 2017
Country/Territory	Taiwan
City	Taichung
Period	11/12/17 → 13/12/17

ASJC Scopus subject areas

Media Technology
Sensory Systems

More information

10.1109/ISM.2017.15

Cite this

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title = "Performance Evaluation of Walking Imagery Training Based on Virtual Environment in Brain-Computer Interfaces",

abstract = "Motor imagery (MI) based on brain computer interfaces (BCIs) have been widely applied for upper limb motor rehabilitation. Due to the fact that a large number of disabled people need to restore or improve walking ability, it is also important to investigate the use of MI-based BCIs for lower limb motor rehabilitation. The brain activity of lower limb MI is more difficult to detect because of low reliability. The purpose of this study is to find a suitable paradigm of walking imagery to achieve better training effect and ensure reliable brain activity. We developed the text-based paradigm and the virtual environment (VE)-based paradigm, and evaluated their performance on identifying walking imagery from idle state.The experimental results provide evidences that the VE-based paradigm could improve the average classification accuracy. This paradigm would induce EEG patterns that make them easier for single-trial detection of walking imagery. This study has the potential to improve the reliability and robustness of walking imagery based BCIs.",

author = "Xiaolu Liu and Shuang Liang and Wenlong Hang and Baiying Lei and Qiong Wang and Jing Qin and Choi, {Kup Sze}",

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Liu, X, Liang, S, Hang, W, Lei, B, Wang, Q, Qin, J & Choi, KS 2017, Performance Evaluation of Walking Imagery Training Based on Virtual Environment in Brain-Computer Interfaces. in Proceedings - 2017 IEEE International Symposium on Multimedia, ISM 2017. vol. 2017-January, IEEE, pp. 25-30, 19th IEEE International Symposium on Multimedia, ISM 2017, Taichung, Taiwan, 11/12/17. https://doi.org/10.1109/ISM.2017.15

Performance Evaluation of Walking Imagery Training Based on Virtual Environment in Brain-Computer Interfaces. / Liu, Xiaolu; Liang, Shuang; Hang, Wenlong et al.
Proceedings - 2017 IEEE International Symposium on Multimedia, ISM 2017. Vol. 2017-January IEEE, 2017. p. 25-30.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

TY - GEN

T1 - Performance Evaluation of Walking Imagery Training Based on Virtual Environment in Brain-Computer Interfaces

AU - Liu, Xiaolu

AU - Liang, Shuang

AU - Hang, Wenlong

AU - Lei, Baiying

AU - Wang, Qiong

AU - Qin, Jing

AU - Choi, Kup Sze

PY - 2017/12/28

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AB - Motor imagery (MI) based on brain computer interfaces (BCIs) have been widely applied for upper limb motor rehabilitation. Due to the fact that a large number of disabled people need to restore or improve walking ability, it is also important to investigate the use of MI-based BCIs for lower limb motor rehabilitation. The brain activity of lower limb MI is more difficult to detect because of low reliability. The purpose of this study is to find a suitable paradigm of walking imagery to achieve better training effect and ensure reliable brain activity. We developed the text-based paradigm and the virtual environment (VE)-based paradigm, and evaluated their performance on identifying walking imagery from idle state.The experimental results provide evidences that the VE-based paradigm could improve the average classification accuracy. This paradigm would induce EEG patterns that make them easier for single-trial detection of walking imagery. This study has the potential to improve the reliability and robustness of walking imagery based BCIs.

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Performance Evaluation of Walking Imagery Training Based on Virtual Environment in Brain-Computer Interfaces

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