{"pk":49642,"title":"Empowering Cross-Patient Adaptive-Length Epilepsy Diagnosis with ECNorm: A Channel-wise Approach","subtitle":null,"abstract":"Automatic seizure detection leveraging artificial intelligence has gained widespread attention. However, existing research has predominantly focused on scenarios with patient-specific and fixed-time lengths, with the practical clinical applications across non-specific patients and variable time lengths remaining underexplored. To address this gap, we introduce a novel method named Electroencephalogram Channel-wise Normalization (ECNorm), designed to thoroughly explore the physical significance and data distribution characteristics of different EEG channels to minimize inter-patient variability. We applied ECNorm to a two-layer LSTM model to facilitate cross-patient adaptive-length epilepsy diagnosis. Ablation studies demonstrate that ECNorm significantly enhances the performance of simple architectures like the two-layer LSTM when compared to batch normalization and layer normalization. Leave-one-out experiments on the public CHB-MIT dataset verify that our approach surpasses existing studies across segments of varying lengths (1 and 100 seconds), establishing a new benchmark for patient-independent automated epilepsy diagnosis.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[{"word":"Event cognition; Electroencephalography (EEG)"}],"section":"Papers with Poster Presentation","is_remote":true,"remote_url":"https://escholarship.org/uc/item/6mt485x8","frozenauthors":[{"first_name":"Kaixuan","middle_name":"","last_name":"WANG","name_suffix":"","institution":"Guangdong Institute of Intelligence Science and Technology","department":""},{"first_name":"Tao","middle_name":"","last_name":"Lu","name_suffix":"","institution":"Guangdong Institute of Intelligence Science and Technology","department":""},{"first_name":"Shangyang","middle_name":"","last_name":"Li","name_suffix":"","institution":"Guangdong Institute of Intelligence Science and Technology","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"2025-01-01T18:00:00Z","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/49642/galley/37604/download/"}]}