Experimental design and signal selection for construction of a robot control system based on EEG signals

• Published in: Robotics and biomimetics Vol. 1; no. 1; p. 1
• Main Authors: Yoshioka, Masataka, Zhu, Chi, Imamura, Kazuyuki, Wang, Feng, Yu, Haoyong, Duan, Feng, Yan, Yuling
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 26.11.2014; Springer Nature B.V
• Subjects: Behavioral Sciences; Engineering; Robotics and Automation; Special Issue on Medical Robotics; Systems Biology; Motor imagery; Robot control; EEG; BMI
• ISSN: 2197-3768; 2197-3768
• DOI: 10.1186/s40638-014-0022-3

Aiming to develop an noninvasive BMI control system with EEG (electroencephalogram) signals to control external devices such as prostheses and robots for rehabilitation and/or power support, four different tasks corresponding to different brain excitation degrees are designed. Their EEG spectra are analyzed with short-time fast Fourier transform (STFFT), and their features of mu and beta rhythms corresponding to the different tasks are extracted. The extracted features are used to control a one-joint robot arm and their corresponding results are compared. The results show that the EEG signal when a subject is holding a weight is comparatively more stable than the EEG signals in other tasks such as motor imagery. This implies an effective way for power assist by EEG signals.