Charles Ákos Szabó1, Lola C Morgan1, Kameel M Karkar1, Linda D Leary1,2, Octavian V Lie1, Michael Girouard3, José E Cavazos3. 1. Department of Neurology, University of Texas Health Science Center at San Antonio and South Texas Comprehensive Epilepsy Center, San Antonio, Texas, U.S.A. 2. Department of Pediatrics, University of Texas Health Science Center at San Antonio and South Texas Comprehensive Epilepsy Center, San Antonio, Texas, U.S.A. 3. Brain Sentinel Inc., San Antonio, Texas, U.S.A.
Abstract
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.
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.
Authors: Daniel M Goldenholz; Robert Moss; David A Jost; Nathan E Crone; Gregory Krauss; Rosalind Picard; Chiara Caborni; Jose E Cavazos; John Hixson; Tobias Loddenkemper; Tracy Dixon Salazar; Laura Lubbers; Lauren C Harte-Hargrove; Vicky Whittemore; Jonas Duun-Henriksen; Eric Dolan; Nitish Kasturia; Mark Oberemk; Mark J Cook; Mark Lehmkuhle; Michael R Sperling; Patricia O Shafer Journal: Epilepsia Date: 2018-03-31 Impact factor: 5.864
Authors: Daniel M Goldenholz; Joseph J Tharayil; Rubin Kuzniecky; Philippa Karoly; William H Theodore; Mark J Cook Journal: Epilepsia Open Date: 2017-01-18
Authors: Jonathan J Halford; Michael R Sperling; Dileep R Nair; Dennis J Dlugos; William O Tatum; Jay Harvey; Jacqueline A French; John R Pollard; Edward Faught; Katherine H Noe; Thomas R Henry; Gina M Jetter; Octavian V Lie; Lola C Morgan; Michael R Girouard; Damon P Cardenas; Luke E Whitmire; Jose E Cavazos Journal: Epilepsia Date: 2017-10-05 Impact factor: 5.864