Robust Semi-synchronous BCI Controller for Brain-Actuated Exoskeleton System

Abstract

In this study, we propose a real-time brain-computer interface (BCI)-based control system for lower limb exoskeleton. Voluntarily induced electroencephalogram (EEG) signal during gait and sit motor imagery (MI) was decoded and translate into the exoskeleton as control commands in real-time. While it is hard to tell when the user engages in the conventional BCI control system, the EEG signal via the user's consecutive eyeblink was used as an initiation of MI in the proposed semi-synchronous control system; hence the EEG decoder is able to denote the transition point. This semi-synchronous BCI control system combines the advantages of asynchronous and synchronous BCI systems by understanding the user's MI environment for robust exception handling. The classifier's flow diagram of the presented BCI control system was described as a finite state machine.