Journal article
Automated Algorithm for Generalized Tonic–Clonic Epileptic Seizure Onset Detection Based on sEMG Zero-Crossing Rate
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 $\pm 50\,\mu \hbox{V}$ . 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.
Language: | English |
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Publisher: | IEEE |
Year: | 2012 |
Pages: | 579-585 |
ISSN: | 15582531 and 00189294 |
Types: | Journal article |
DOI: | 10.1109/TBME.2011.2178094 |
ORCIDs: | Sørensen, Helge Bjarup Dissing |
Accelerometers Adult Algorithms Child Diagnosis, Computer-Assisted Electrodes Electromyography Epilepsy, Tonic-Clonic Female Humans Male Middle Aged Monitoring Muscles Seizures Sensitivity Sensitivity and Specificity Signal Processing, Computer-Assisted Training automated algorithm biomedical electrodes clinical implementation deltoid muscle detection latency electromyography false detection rate feature extraction frequency 150 Hz generalized tonic-clonic epileptic seizure onset detection genetic algorithms high-pass filtering high-pass filters medical disorders medical signal processing neurophysiology patient monitoring portable device portable instruments robust generic algorithm sEMG electrode sEMG zero-crossing rate seizure detection sensitivity surface electromyography (sEMG) surface electromyography signals time 13.7 s time 24 h tonic–clonic zero-crossing count monitoring