Abstracts

Rationale: There is a growing need for non-EEG, wearable devices to automatically monitor epileptic seizures in ambulatory settings. Efforts to date have focused on the development of devices to detect convulsive seizures, such as the FDA-approved smart watch Embrace by Empatica (Onorati et al, Epilepsia 2017, 58, 11). However, Embrace was not designed to detect nonconvulsive seizures such as focal seizures with impaired awareness (FIAS). Few works have investigated the feasibility of nonconvulsive seizure monitoring based on wrist-worn sensors (Thome-Souza et al 2014, AES; Poh et al, Neurology 2012, 78(23); Cogan et al, Int J Neural Syst 2017, 27, 1650031). This work characterizes autonomic changes measured at the wrist at the time of FIAS as a step toward providing a future automated monitor of nonconvulsive seizures. Methods: A cohort of 3 children and 9 adults (ages: 10 to 52 years, median: 37 years) experienced a total of 40 FIAS in Epilepsy Monitoring Units while wearing the Empatica E4 wristband. The E4’s sensors provided heart rate (HR) from photoplethysmography (PPG), as well as electrodermal activity (EDA) and accelerometer activity.  Seizures were clinically labeled using video-EEG. A significant EDA response (EDR) after the seizure onset was detected offline, defined as the EDA level above two times the standard deviation of a 15-sec EDA baseline, drawn 1 min before the seizure. HR patterns 5 seconds before and 10 seconds after the seizure onset were analyzed in the time domain and compared to baseline values (1 min before onset). Results: HR data showed an increase around the seizure onset in 80% of the seizures. The derivative of the HR in a 15-sec time window around the seizure onset was significantly higher (mean increase of 4 bpm/s, p< 0.001) than the baseline values. Overall, 11 out of 40 (28%) of the recorded FIAS showed a significant EDR (median amplitude relative increase: 181%). Interestingly, 75% of patients who usually experience both FIAS and generalized seizures exhibited an EDR with their FIAS. The peak of the EDR occurred 5 min (median value, range: 18 secs to 10 min) after the seizure onset and the EDR lasted 11 min (median value, range: 30 secs to 30 min). Conclusions: We reported for the first time an analysis of HR and EDA changes related to nonconvulsive seizures recorded with the E4 wristband. Most of the FIAS had a statistically significant HR increase around the seizure onset, in line with earlier observations (Cogan et al 2017). The automatic detection of significant EDR’s in our dataset was challenged by night time EDA sleep storm activation observed in the peri-ictal baseline window. The differences in cohort characteristics, sleep storm activity, and computational method may account for the fewer significantly-sized EDR’s found here than observed previously (Thome-Souza et al 2014, Poh et al 2012). A combination of HR and EDA signals could potentially be used for real-time detection of FIAS especially during rest periods. This preliminary analysis lays the groundwork for further work on a nonconvulsive seizure detection and classification system with multimodal wearable devices.   Funding: No funds