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Electromyography-based seizure detector: Preliminary results comparing a generalized tonic-clonic seizure detection algorithm to video-EEG recordings - 2015

Electromyography-Based Seizure Detector: Preliminary Results Comparing A Generalized Tonic-Clonic Seizure Detection Algorithm To Video-Eeg Recordings

Research Area:  Machine Learning


Automatic detection of generalized tonic-clonic seizures (GTCS) will facilitate patient monitoring and early intervention to prevent comorbidities, recurrent seizures, or death. Brain Sentinel (San Antonio, Texas, USA) developed a seizure-detection algorithm evaluating surface electromyography (sEMG) signals during GTCS. This study aims to validate the seizure-detection algorithm using inpatient video-electroencephalography (EEG) monitoring. sEMG was recorded unilaterally from the biceps/triceps muscles in 33 patients (17white/16 male) with a mean age of 40 (range 14-64) years who were admitted for video-EEG monitoring. Maximum voluntary biceps contraction was measured in each patient to set up the baseline physiologic muscle threshold. The raw EMG signal was recorded using conventional amplifiers, sampling at 1,024 Hz and filtered with a 60 Hz noise detection algorithm before it was processed with three band-pass filters at pass frequencies of 3-40, 130-240, and 300-400 Hz. A seizure-detection algorithm utilizing Hotelling-s T-squared power analysis of compound muscle action potentials was used to identify GTCS and correlated with video-EEG recordings.In 1,399 h of continuous recording, there were 196 epileptic seizures (21 GTCS, 96 myoclonic, 28 tonic, 12 absence, and 42 focal seizures with or without loss of awareness) and 4 nonepileptic spells. During retrospective, offline evaluation of sEMG from the biceps alone, the algorithm detected 20 GTCS (95%) in 11 patients, averaging within 20 s of electroclinical onset of generalized tonic activity, as identified by video-EEG monitoring. Only one false-positive detection occurred during the postictal period following a GTCS, but false alarms were not triggered by other seizure types or spells.Brain Sentinel-s seizure detection algorithm demonstrated excellent sensitivity and specificity for identifying GTCS recorded in an epilepsy monitoring unit. Further studies are needed in larger patient groups, including children, especially in the outpatient setting.


Author(s) Name:  Charles Ákos Szabó, Lola C Morgan, Kameel M Karkar, Linda D Leary, Octavian V Lie, Michael Girouard, José E Cavazos

Journal name:  Epilepsia

Conferrence name:  

Publisher name:  pubmed

DOI:  10.1111/epi.13083

Volume Information:  Volume 56, Issue 9