Accurate detection of typical absence seizures in adults and children using a two-channel electroencephalographic wearable behind the ears

Abstract

Objective: Patients with absence epilepsy sensitivity <10% of their absences. The clinical gold standard to assess absence epilepsy is a 24-h electroencephalographic (EEG) recording, which is expensive, obtrusive, and time-consuming to review. We aimed to (1) investigate the performance of an unobtrusive, two-channel behind-the-ear EEG-based wearable, the Sensor Dot (SD), to detect typical absences in adults and children; and (2) develop a sensitive patient-specific absence seizure detection algorithm to reduce the review time of the recordings. Methods: We recruited 12 patients (median age = 21 years, range = 8–50; seven female) who were admitted to the epilepsy monitoring units of University Hospitals Leuven for a 24-h 25-channel video-EEG recording to assess their refractory typical absences. Four additional behind-the-ear electrodes were attached for concomitant recording with the SD. Typical absences were defined as 3-Hz spike-and-wave discharges on EEG, lasting 3 s or longer. Seizures on SD were blindly annotated on the full recording and on the algorithm-labeled file and consequently compared to 25-channel EEG annotations. Patients or caregivers were asked to keep a seizure diary. Performance of the SD and seizure diary were measured using the F1 score. Results: We concomitantly recorded 284 absences on video-EEG and SD. Our absence detection algorithm had a sensitivity of.983 and false positives per hour rate of.9138. Blind reading of full SD data resulted in sensitivity of.81, precision of.89, and F1 score of.73, whereas review of the algorithm-labeled files resulted in scores of.83,.89, and.87, respectively. Patient self-reporting gave sensitivity of.08, precision of 1.00, and F1 score of.15. Significance: Using the wearable SD, epileptologists were able to reliably detect typical absence seizures. Our automated absence detection algorithm reduced the review time of a 24-h recording from 1-2 h to around 5–10 min.