title: Epileptic seizure detection from ECoG using recurrence time statistics.
abstract: A recurrence time statistics T1 is defined and used as a feature extraction method for seizure detection. The preliminary data shows that during seizure T1 generates a peak and this peak clearly distinguishes the seizure state from background activity. When applied to multi-channel ECoG recordings, the spatial-temporal signature of T1 can be clearly observed to discriminate seizures. The T1 feature was used for automated seizure detection on two sets of long term monitoring ECoG data. The detection probability reached 97% with a 0.29 per hour average false alarm rate.
authors.affiliation: Dept. of Electr. & Comput. Eng., Florida Univ., Gainesville, FL, USA.
authors.forename: Hui
authors.initials: H
authors.lastname: Liu
authors.forename: J B
authors.initials: JB
authors.lastname: Gao
authors.forename: Kenneth E
authors.initials: KE
authors.lastname: Hild
authors.forename: José C
authors.initials: JC
authors.lastname: Príncipe
authors.forename: J
authors.initials: J
authors.lastname: Chris Sackellares