Development of a support robot hand system using SSVEP

Zixun He¹, Yuusuke Watanabe¹, Rezenko Roman Yurievich¹,

Yuta Ogai¹, Yousun Kang², and Duk Shin¹⁺

¹Department of Electronics and Mechatronics, Tokyo Polytechnic University, Kanagawa, 243-0297, Japan

{He, Watanabe, Roman}@st.t-kougei.ac.jp, {ogai, d.shin}@em.t-kougei.ac.jp

²Department of Applied Computer Science, Tokyo Polytechnic University, Kanagawa, 243-0297, Japan

yskang@cs.t-kougei.ac.jp

Abstract

Recently, the Brain-Computer Interface (BCI) system could support various aspects of everyday life of elderly and disabled people. In this research, we developed a noninvasive BCI system that controls the robot hand using induced brain waves Steady-State Visual Evoked Potential (SSVEP) in order to improve the quality of life of patients with hands or arms deficient or impaired. This BCI 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 and arm rotation of the robot hand. 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 the average accuracy of 97% in a time window length of 4 s and the use of three harmonics..

Keywords: Brain-Computer Interface (BCI), Steady-State Visual Evoked Potential (SSVEP),
robot control

+:Corresponding author: Duk Shin

1583, Tokyo Polytechnic University, Atsugi, Kanagawa, 243-0297, Japan, Tel: +81-462-42-9562

IT Convergence Practice (INPRA), Vol. 6, No. 4, pp. 1-11, December 2018 [pdf]