EEG-modulated robotic rehabilitation system for upper extremity

• Main Authors: Baoguo Xu, Aiguo Song, Guopu Zhao, Jia Liu, Guozheng Xu, Lizheng Pan, Renhuan Yang, Huijun Li, Jianwei Cui
• Format: Article
• Language: English
• Published: Taylor & Francis Group 2018-05-01
• Series: Biotechnology & Biotechnological Equipment
• Subjects: Neurorehabilitation robot; stroke therapy; fuzzy logic; motor imagery
• Online Access: http://dx.doi.org/10.1080/13102818.2018.1437569

This paper presents a novel electroencephalogram (EEG)-triggered upper extremity training system. Motor imagery EEG of upper extremity movements is adopted to trigger the Barrett WAM to perform rehabilitation training for patients with stroke. We focus on fully exploring the patient's movement intention and attention from movement imagination EEG and controlling the WAM robot to perform training effectively. A position controller based on fuzzy logic is presented for the rehabilitation system to drive the WAM robot smoothly. Experimental results with seven participants are reported to show the feasibility and effectiveness of the robotic therapy system.