Brain Computer Interface for Epilepsy Treatment

A brain computer interface (BCI) is a communication system converting neural activities into signals that can control computer cursors or external devices (Fetz, 2007). BCI was initially and mainly employed for patients with severe motor disorders such as amyotrophic lateral sclerosis (ALS) by providing non-muscular bidirectional communication and control. How‐ ever, the application of BCI has been extended to control various EEG signals for therapeutic purposes, such as seizure control in epilepsy patients. Although such BCIs did not demonstrate rapid control as in non-muscular communication, it still assumes that EEG based bidirectional control is possible (Wolpaw et al., 2002). More specifically, a BCI in epilepsy research, as in the current chapter, refers to a communication system capable to acquire signal and to implement real-time seizure detection/prediction and contingent delivery of warning stimuli or therapies such as electrical stimulation to control seizures (see the diagram). Such systems became feasible with technological development, and have been implemented in animal and human to control seizures. In the current chapter we will first give an overview of application of BCI, especially with deep brain stimulation in epilepsy research. Then we will discuss different components of a BCI system: input (signal acquisition), algorithm (seizure detection/predic‐ tion) and output (application and users), in particular stressing some important issues on BCI performance.