Chun Sing Louis Tsui

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This paper presents a novel hands-free control system for an electric-powered wheelchair, which is based on EMG (Electromyography) signals recorded from eyebrow muscle activity. By using a simple CyberLink [1] device, one-dimensional continuous EMG signals are obtained, analysed, and then translated into multi-directional control commands (forward, left,(More)
Due to the non-stationarity of EEG signals, online training and adaptation is essential to EEG based brain-computer interface (BCI) systems. Asynchronous BCI offers more natural human-machine interaction, but it is a great challenge to train and adapt an asynchronous BCI online because the user's control intention and timing are usually unknown. This paper(More)
This paper presents a simple self-paced motor imagery based brain-computer interface (BCI) to control a robotic wheelchair. An innovative control protocol is proposed to enable a 2-class self-paced BCI for wheelchair control, in which the user makes path planning and fully controls the wheelchair except for the automatic obstacle avoidance based on a laser(More)
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