Host: Japan Society for Fuzzy Theory and Intelligent Informatics (SOFT)
Name : 34th Fuzzy System Symposium
Number : 34
Location : [in Japanese]
Date : September 03, 2018 - September 05, 2018
Recently, SSVEP- based BMI could support various aspects of everyday life of elderly and disabled people. In this research, we developed a noninvasive BMI system that controls the robot hand using induced brain waves SSVEP in order to improve the quality of life(QOL) of patients with hands or arms deficient or impaired. This BMI system consists of visual stimulator, 6 degree of freedom (DOF) robot hand, an EEG recorder and a laptop for processing data. The subject induces the corresponding SSVEP signal by seeing one target in the three visual stimuli (5Hz, 6Hz, 7Hz) representing the motion: grip, pinch, arm rotation of the robot hand, respectively. The detected SSVEP signal is classified by canonical correlation analysis (CCA). The robot hand is operated by converting the SSVEP into the control signal according to the classification result. The results show that the proposed BCI system has a high performance, achieving an accuracy of 93% in a window length of 1 s and the second harmonics.
