title: Online Automated Seizure Detection in Temporal Lobe Epilepsy Patients Using Single-lead ECG.
abstract: Automated seizure detection in a home environment has been of increased interest the last couple of decades. The electrocardiogram is one of the signals that is suited for this application. In this paper, a new method is described that classifies different heart rate characteristics in order to detect seizures from temporal lobe epilepsy patients. The used support vector machine classifier is trained on data from other patients, so that the algorithm can be used directly from the start of each new recording. The algorithm was tested on a dataset of more than 918[Formula: see text]h of data coming from 17 patients containing 127 complex partial and generalized partial seizures. The algorithm was able to detect 81.89% of the seizures, with on average 1.97 false alarms per hour. These results show a strong drop in the number of false alarms of more than 50% compared to other heart rate-based patient-independent algorithms from the literature, at the expense of a slightly higher detection delay of 17.8s on average.
authors.affiliation: 1 Department of Electrical Engineering, KU Leuven, Kasteelpark Arenberg 10, Box 2446, Leuven, 3000, Belgium.|2 imec, Leuven, Belgium.
authors.forename: Thomas
authors.initials: T
authors.lastname: De Cooman
authors.affiliation: 1 Department of Electrical Engineering, KU Leuven, Kasteelpark Arenberg 10, Box 2446, Leuven, 3000, Belgium.|2 imec, Leuven, Belgium.
authors.forename: Carolina
authors.initials: C
authors.lastname: Varon
authors.affiliation: 1 Department of Electrical Engineering, KU Leuven, Kasteelpark Arenberg 10, Box 2446, Leuven, 3000, Belgium.|2 imec, Leuven, Belgium.
authors.forename: Borbála
authors.initials: B
authors.lastname: Hunyadi
authors.affiliation: 3 Department of Neurology, UZ Leuven and KU Leuven, Herestraat 49, Leuven, 3000, Belgium.
authors.forename: Wim
authors.initials: W
authors.lastname: Van Paesschen
authors.affiliation: 4 Department of Child Neurology, UZ Leuven and KU Leuven, Herestraat 49, Leuven, 3000, Belgium.
authors.forename: Lieven
authors.initials: L
authors.lastname: Lagae
authors.affiliation: 1 Department of Electrical Engineering, KU Leuven, Kasteelpark Arenberg 10, Box 2446, Leuven, 3000, Belgium.|2 imec, Leuven, Belgium.
authors.forename: Sabine
authors.initials: S
authors.lastname: Van Huffel
mesh_terms: D000293:Adolescent; D000328:Adult; D000465:Algorithms; D058256:Brain Waves; D002648:Child; D004562:Electrocardiography; D004569:Electroencephalography; D004833:Epilepsy, Temporal Lobe / Q000503:physiopathology*; D005260:Female; D006339:Heart Rate / Q000502:physiology*; D006801:Humans; D008297:Male; D008875:Middle Aged; D009862:Online Systems; D012815:Signal Processing, Computer-Assisted; D060388:Support Vector Machine
keywords: Epilepsy; electrocardiogram; home monitoring; seizure detection