Data from: Ictal quantitative surface electromyography correlates with postictal EEG suppression

Objective: To test the hypothesis that neurophysiological biomarkers of muscle activation during convulsive seizures reveal seizure severity, and to determine whether automatically computed surface electromyography (EMG) parameters during seizures can predict postictal generalized EEG suppression (PGES) indicating increased risk for sudden unexpected death in epilepsy (SUDEP). Wearable EMG devices have been clinically validated for automated detection of generalized tonic-clonic seizures (GTCS). Our goal was to use automated EMG measurements for seizure-characterization and risk-assessment. Methods: Quantitative parameters were automatically computed from surface EMG recorded during convulsive seizures, from deltoid and brachial biceps muscles, in patients admitted to long-term video-EEG monitoring. Parameters evaluated were: the durations of the seizure phases (tonic, clonic), durations of the clonic bursts and silent periods, as well as the dynamics of their evolution (slope). We compared them with the duration of the PGES. Results: We found significant correlations between automatically computed EMG parameters and the duration of PGES (p