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Mechatronic Implementation and Trajectory Tracking Validation of a BCI-based Human-wheelchair Interface

Authors :
Yu-Cheng Kuo
Chun-Ju Wu
Jian-Wen Chen
Yi-Tseng Lin
Chung-Hsien Kuo
Source :
BioRob
Publication Year :
2020
Publisher :
IEEE, 2020.

Abstract

This paper presents a mechatronic P300-based brain computer interface (BCI) for wheelchair control applications. A translucent visual stimulus panel (TVSP) is set up in front of the wheelchair to provide an intuitive P300 visual stimulus operation as well as to realize the see-through scene during operating wheelchairs. In this research, a micro projector is utilized to produce flickering visual stimuli on the display board which is 35cm away from the user. To improve the information transfer rate (ITR), a spatial filter based on Canonical Correlation Analysis (CCA) and Support Vector Machine (SVM) were also applied to this work to improve the performance of BCI classification. The result of experiments showed that the proposed BCI is with 88.2% in accuracy and 22.97 bits/min information transfer rate in average received from ten subjects. In ground truth experiments of practical trajectory tracking, the root mean squared error (RMSE) of P300 BCI are 12.11cm in “U” trajectory test.

Details

Database :
OpenAIRE
Journal :
2020 8th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics (BioRob)
Accession number :
edsair.doi...........d4e848a7a668afceb927ce5750378c8f
Full Text :
https://doi.org/10.1109/biorob49111.2020.9224373