Supervised Learning in Automatic Channel Selection for Epileptic Seizure Detection

31 Jan 2017Nhan TruongLevin KuhlmannMohammad Reza BonyadiJiawei YangAndrew FaulksOmid Kavehei

Detecting seizure using brain neuroactivations recorded by intracranial electroencephalogram (iEEG) has been widely used for monitoring, diagnosing, and closed-loop therapy of epileptic patients, however, computational efficiency gains are needed if state-of-the-art methods are to be implemented in implanted devices. We present a novel method for automatic seizure detection based on iEEG data that outperforms current state-of-the-art seizure detection methods in terms of computational efficiency while maintaining the accuracy... (read more)

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