Electroencephalogram-based brain-computer interface systems for controlling rehabilitative devices

Brain signals can be acquired from various methods, including magnetoencephalogram, electrocorticogram, functional magnetic resonance imaging, functional near-infrared spectroscopy, and electroencephalogram (EEG). Among all the methods, the brain signals acquired from the EEG signals have been much explored in the last few decades. This is attributed to the low cost, very user-friendly, and noninvasive nature of the instruments for acquiring the clinical EEG signals. Hence, these systems have been explored to devise brain-computer interface (BCI) systems. The BCI systems have been successfully used in various areas, including home automation. Taking a cue from this, many researchers working in the field of assistive technologies have tried to extend the applications of BCI systems in controlling assistive devices like automated wheelchairs, home automation systems for the severely disabled, and limb prostheses. In this chapter, we have discussed the motivation behind using the EEG-based BCI systems, the EEG signal acquisition and processing techniques, and the applications of the EEG-based BCI systems in designing control systems for assistive devices.