TY - JOUR
T1 - Electromyography-based seizure detector
T2 - Preliminary results comparing a generalized tonic-clonic seizure detection algorithm to video-EEG recordings
AU - Szabõ, Charles Ákos
AU - Morgan, Lola C.
AU - Karkar, Kameel M.
AU - Leary, Linda D.
AU - Lie, Octavian V.
AU - Girouard, Michael
AU - Cavazos, José E.
N1 - Publisher Copyright:
© 2015 The Authors. Epilepsia published by Wiley Periodicals Inc. on behalf of International League Against Epilepsy.
PY - 2015/9/1
Y1 - 2015/9/1
N2 - Summary Objective 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. Methods 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. Results 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. Significance 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.
AB - Summary Objective 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. Methods 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. Results 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. Significance 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.
KW - Generalized tonic-clonic seizures
KW - Seizure detection devices
KW - Sensitivity and specificity
KW - Surface-electromyography
KW - Video-electroencephalography
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U2 - 10.1111/epi.13083
DO - 10.1111/epi.13083
M3 - Article
C2 - 26190150
AN - SCOPUS:84940961024
SN - 0013-9580
VL - 56
SP - 1432
EP - 1437
JO - Epilepsia
JF - Epilepsia
IS - 9
ER -