An Eeg-Controlled Wheelchair Using Eye Movements

This paper proposes a threshold algorithm to extract features and then create standard thresholds of EEG online signals using eye movements. Based on the standard thresholds, an electrical wheelchair can be controlled to reach the desired target. In this project, a Hamming band-pass filter is applied to detect noise of EEG signal. Moreover, calculation of blink-times and detection of confusion between left glance and right glance signals program are built and added to increase the accuracy of the wheelchair control. Additionally, a quality testing program is also built in Labview environment to improve effort of data collection. Finally, experimental results of controlling the electrical wheelchair in indoor environments demonstrated the effectiveness of the proposed method.