Design and evaluation of a motor imagery electroencephalogram-controlled robot system

Autor: Baoguo Xu, Aiguo Song, Guopu Zhao, Guozheng Xu, Lizheng Pan, Renhuan Yang, Huijun Li, Jianwei Cui
Jazyk: angličtina
Rok vydání: 2015
Předmět:
Zdroj: Advances in Mechanical Engineering, Vol 7 (2015)
Druh dokumentu: article
ISSN: 1687-8140
16878140
DOI: 10.1177/1687814015573607
Popis: Brain–computer interface provides a new communication channel to control external device by directly translating the brain activity into commands. In this article, as the foundation of electroencephalogram-based robot-assisted upper limb rehabilitation therapy, we report on designing a brain–computer interface–based online robot control system which is made up of electroencephalogram amplifier, acquisition and experimental platform, feature extraction algorithm based on discrete wavelet transform and autoregressive model, linear discriminant analysis classifier, robot control board, and Rhino XR-1 robot. The performance of the system has been tested by 30 participants, and satisfactory results are achieved with an average error rate of 8.5%. Moreover, the advantage of the feature extraction method was further validated by the Graz data set for brain–computer interface competition 2003, and an error rate of 10.0% was obtained. This method provides a useful way for the research of brain–computer interface system and lays a foundation for brain–computer interface–based robotic upper extremity rehabilitation therapy.
Databáze: Directory of Open Access Journals