Abstract: An ambulatory patient-specific epileptic seizure detector based on scalp EEG signals is presented. A method for selecting a patient-specific subset of electrodes from a plurality of m EEG channels needed to detect an epileptic seizure in the patient is also presented. Seizure EEG data is collected from the plurality of m EEG channels. An effective subset n of the channels of the plurality of m EEG channels is selected using recursive feature processing and a detector is constructed in response to the subset n of channels. The performance of the detector in detecting seizures is then estimated.