title: Automated algorithm for generalized tonic-clonic epileptic seizure onset detection based on sEMG zero-crossing rate.
abstract: Patients are not able to call for help during a generalized tonic-clonic epileptic seizure. Our objective was to develop a robust generic algorithm for automatic detection of tonic-clonic seizures, based on surface electromyography (sEMG) signals suitable for a portable device. Twenty-two seizures were analyzed from 11 consecutive patients. Our method is based on a high-pass filtering with a cutoff at 150 Hz, and monitoring a count of zero crossings with a hysteresis of ±50 μV . Based on data from one sEMG electrode (on the deltoid muscle), we achieved a sensitivity of 100% with a mean detection latency of 13.7 s, while the rate of false detection was limited to 1 false alarm per 24 h. The overall performance of the presented generic algorithm is adequate for clinical implementation.
authors.affiliation: Biomedical Department of Electrical Engineering, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark. isaconradsen@gmail.com
authors.forename: Isa
authors.initials: I
authors.lastname: Conradsen
authors.forename: Sándor
authors.initials: S
authors.lastname: Beniczky
authors.forename: Karsten
authors.initials: K
authors.lastname: Hoppe
authors.forename: Peter
authors.initials: P
authors.lastname: Wolf
authors.forename: Helge B D
authors.initials: HB
authors.lastname: Sorensen
mesh_terms: D000328:Adult; D000465:Algorithms; D002648:Child; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004576:Electromyography / Q000379:methods*; D004830:Epilepsy, Tonic-Clonic / Q000175:diagnosis* / Q000503:physiopathology; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D012640:Seizures / Q000175:diagnosis* / Q000503:physiopathology; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted