Automated seizure detection with noninvasive wearable devices: A systematic review and meta-analysis.

Objective: This study was undertaken to review the reported performance of noninvasive wearable devices in detecting epileptic seizures and psychogenic nonepileptic seizures (PNES).

Methods: We conducted a systematic review and meta-analysis of studies reported up to November 15, 2021. We included studies that used video-electroencephalographic (EEG) monitoring as the gold standard to determine the sensitivity and false alarm rate (FAR) of noninvasive wearables for automated seizure detection.

Results: Twenty-eight studies met the criteria for the systematic review, of which 23 were eligible for meta-analysis. These studies (1269 patients in total, median recording time = 52.9 h per patient) investigated devices for tonic-clonic seizures using wrist-worn and/or ankle-worn devices to measure three-dimensional accelerometry (15 studies), and/or wearable surface devices to measure electromyography (eight studies). The mean sensitivity for detecting tonic-clonic seizures was .91 (95% confidence interval [CI] = .85-.96, I  = 83.8%); sensitivity was similar between the wrist-worn (.93) and surface devices (.90). The overall FAR was 2.1/24 h (95% CI = 1.7-2.6, I  = 99.7%); FAR was higher in wrist-worn (2.5/24 h) than in wearable surface devices (.96/24 h). Three of the 23 studies also detected PNES; the mean sensitivity and FAR from these studies were 62.9% and .79/24 h, respectively. Four studies detected both focal and tonic-clonic seizures, and one study detected focal seizures only; the sensitivities ranged from 31.1% to 93.1% in these studies.

Significance: Reported noninvasive wearable devices had high sensitivity but relatively high FARs in detecting tonic-clonic seizures during limited recording time in a video-EEG setting. Future studies should focus on reducing FAR, detection of other seizure types and PNES, and longer recording in the community.