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

Jian Wen Chen, Chun Ju Wu, Yi Tseng Lin, Yu Cheng Kuo, Chung Hsien Kuo*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

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.

Original languageEnglish
Title of host publication2020 8th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics, BioRob 2020
PublisherIEEE Computer Society
Pages304-309
Number of pages6
ISBN (Electronic)9781728159072
DOIs
StatePublished - 11 2020
Externally publishedYes
Event8th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics, BioRob 2020 - New York City, United States
Duration: 29 11 202001 12 2020

Publication series

NameProceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics
Volume2020-November
ISSN (Print)2155-1774

Conference

Conference8th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics, BioRob 2020
Country/TerritoryUnited States
CityNew York City
Period29/11/2001/12/20

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

Keywords

  • Algorithms and machine learning
  • Brain-machine interfaces
  • Human-machine interfaces

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