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Journal Article

Citation

Zhang R, Li Y, Yan Y, Zhang H, Wu S, Yu T, Gu Z. IEEE Trans. Neural Syst. Rehabil. Eng. 2015; 24(1): 128-139.

Copyright

(Copyright © 2015, IEEE (Institute of Electrical and Electronics Engineers))

DOI

10.1109/TNSRE.2015.2439298

PMID

26054072

Abstract

The concept of controlling a wheelchair using brain signals is promising. However, the continuous control of a wheelchair based on unstable and noisy electroencephalogram (EEG) signals is unreliable and generates a significant mental burden for the user. A feasible solution is to integrate a braincomputer interface (BCI) with automated navigation techniques. This paper presents a brain-controlled intelligent wheelchair with the capability of automatic navigation. Using an autonomous navigation system, candidate destinations and waypoints are automatically generated based on the existing environment. The user selects a destination using a motor imagery (MI)-based or P300-based BCI. According to the determined destination, the navigation system plans a short and safe path and navigates the wheelchair to the destination. During the movement of the wheelchair, the user can issue a stop command with the BCI. Using our system, the mental burden of the user can be substantially alleviated. Furthermore, our system can adapt to changes in the environment. Two experiments based on MI and P300 were conducted to demonstrate the effectiveness of our system.


Language: en

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