ENCEVIS Automated Seizure Detection Performance: Influence of Seizure Characteristics

Abstract

Background: Long-term video-EEG monitoring (LTM) in dedicated epilepsy units increases the chances of capturing epileptic seizures. It is thus essential for diagnosing epilepsy, seizure classification, and patient selection for epilepsy surgery. LTM recordings generate vast data that require EEG experts to assess visually, which is time-consuming and expensive. Several automatic seizure detection systems based on scalp EEG are available. One such system is the ENCEVIS. Our study approaches how the ENCEVIS software could be used in an EMU setting. We covered a wide range of epilepsy syndromes, providing excellent insight into the sensitivity of ENCEVIS across various forms of epilepsy commonly seen in clinical practice. Objectives: To assess seizure characteristics that influence the ENCEVIS's performance, we compared its performance to conventional EEG review by clinical physiologists according to seizure onset localization, duration, electrographic changes, and semiology. Methods: We prospectively included 266 anonymous video-EEG recordings (>4h) from 263 individuals ages 4-67 in the study. The final database contained 112 seizures lasting more than 5 seconds from 43 ictal recordings. Recordings with non-epileptic paroxysmal events were excluded. Two independent EEG experts visually analyzed and assessed ENCEVIS. They defined true positive, false negative, and false positive seizure detections. Results: Seizure duration (<10 sec 6.3%, >60 sec. 63.9% (p<0.05) influenced ENCEVIS sensitivity. GTCS and FB-TCS were detected with 100% sensitivity. Focal seizures with impaired awareness also were detected as statistically reliable at 69.5% (P<005). Sensitivities for focal aware seizure and generalized tonic seizures were 26.7% and 23.1%, respectively. Conclusions: ENCEVIS software does not perform as well in real-life scenarios as clinical physiologists do. The algorithm is most sensitive to longer- duration focal seizures with impaired awareness, GTCS, and FB-TCS seizures. Sensitivity is the lowest for shorter generalized tonic and focal aware seizures. This assessment may give future users helpful insight into this software's strengths and weaknesses and help further improve the algorithm.