NDLI: Mechanical vibrotactile stimulation effect in motor imagery based brain-computer interface

Content Provider	IEEE Xplore Digital Library
Author	Lin Yao Xinjun Sheng Jianjun Meng Dingguo Zhang Xiangyang Zhu
Copyright Year	2013
Description	Author affiliation: State Key Lab. of Mech. Syst. & Vibration, Shanghai Jiao Tong Univ., Shanghai, China (Lin Yao; Xinjun Sheng; Jianjun Meng; Dingguo Zhang; Xiangyang Zhu)
Abstract	Sensory stimulation played a critical role in both motivating subject's anticipation in brain-computer interface but also enhancing the sensory-motor interaction and closing the sensory motor loop. In this paper, mechanical vibrotactile stimulation effect in motor imagery was evaluated on 10 healthy subjects, and preliminary results showed that 5 subjects would achieve a reliable control above 80% with sensory stimulation as comparable with motor imagery without any stimulation. Besides, 3 subjects reached a better control with approximately 70% as compared with a chance level of 50% in motor imagery without sensory stimulation. Further analysis showed subject who was poor in conventional motor imagery condition exhibited enhanced $R^{2}$ value distribution in motor imagery with sensory stimulation condition. Meanwhile there was sensorimotor rhythmic enhancement both at upper alpha band and upper beta band in some subjects. But these rhythmic changes resulted performance reduction as incongruence of training and testing sets effect from off-line analysis. This research provided some guidance in integration of the sensory stimulation channel with motor imagery based BCI system.
Starting Page	2772
Ending Page	2775
File Size	753087
Page Count	4
File Format	PDF
ISBN	9781457702167
ISSN	1557170X
DOI	10.1109/EMBC.2013.6610115
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-03
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Accuracy Robot sensing systems Testing Training Electroencephalography Decoding Vibrations
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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