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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 device, one-dimensional continuous EMG signals are obtained, analysed, and then translated into multi-directional control commands (forward, left, right,(More)
This paper investigates manifestation of fatigue in myoelectric signals during dynamic contractions produced whilst playing PC games. The hand's myoelectric signals were collected in 26 independent sessions with 10 subjects. Two methods, spectral analysis and time-scale analysis, were applied to compute signal frequency and least-square linear regression(More)
Due to the non-stationarity of EEG signals, online training and adaptation are essential to EEG based brain-computer interface (BCI) systems. Self-paced BCIs offer more natural human-machine interaction than synchronous BCIs, but it is a great challenge to train and adapt a self-paced BCI online because the user's control intention and timing are usually(More)
This paper presents a novel user interface suitable for adaptive Brain Computer Interface (BCI) system. A customized self-paced BCI architecture is introduced where the system combines onset detection system along with an adaptive classifier working in parallel. An unsupervised adaptive method based on sequential expectation maximization for Gaussian(More)
Conditional random fields (CRFs) are demonstrated to be a discriminative model able to exploit the temporal properties of EEG data obtained during synchronous three-class motor-imagery-based brain-computer interface experiments. The advantages of CRFs over the hidden Markov model (HMM) are both theoretical and practical. Theoretically, CRFs focus on(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)
—A novel presentation for channel selection problem in Brain-Computer Interfaces (BCI) is introduced here. Continuous presentation in a projected two-dimensional space of the Electroencephalograph (EEG) cap is proposed. A multi-objective particle swarm optimization method (D 2 M OP SO) is employed where particles move in the EEG cap space to locate the(More)