Epileptic seizure forecasting with wearable-based nocturnal sleep features.

ABSTRACT:

Objective

Non-invasive biomarkers have recently shown promise for seizure forecasting in people with epilepsy. In this work, we developed a seizure-day forecasting algorithm based on nocturnal sleep features acquired using a smart shirt.

Methods

Seventy-eight individuals with epilepsy admitted to the Centre hospitalier de l'Université de Montréal epilepsy monitoring unit wore the Hexoskin biometric smart shirt during their stay. The shirt continuously measures electrocardiography, respiratory, and accelerometry activity. Ten sleep features, including sleep efficiency, sleep latency, sleep duration, time spent in non-rapid eye movement sleep (NREM) and rapid eye movement sleep (REM), wakefulness after sleep onset, average heart and breathing rates, high-frequency heart rate v

SUBMITTER: Ding TY 

PROVIDER: S-EPMC11450616 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature