{"id":32374,"date":"2026-01-21T17:01:51","date_gmt":"2026-01-21T17:01:51","guid":{"rendered":"https:\/\/lamarr-institute.org\/publication\/visor-visual-seizure-onset-detection-personalized-for-epilepsy-patients\/"},"modified":"2026-06-08T13:20:02","modified_gmt":"2026-06-08T13:20:02","slug":"visor-visual-seizure-onset-detection-personalized-for-epilepsy-patients","status":"publish","type":"publication","link":"https:\/\/lamarr-institute.org\/de\/publication\/visor-visual-seizure-onset-detection-personalized-for-epilepsy-patients\/","title":{"rendered":"{VISOR}: {VIsual} Seizure Onset Detection {PeRsonalized} for\u00a0Epilepsy Patients"},"content":{"rendered":"<p>The onset detection of epileptic seizures from multivariate Electroencephalogram ({EEG}) data is a challenging task. The variation in seizure patterns across patients and epilepsy types makes it particularly difficult to create a generic solution. Existing approaches indicate low recall due to their inability to capture complex seizure onset patterns. In this paper, we propose {VISOR} \u2013 a novel approach to detect the onset of epileptic seizures based on novel patient profiles and visual, personalized feature representations. {VISOR} leverages a vision transformer model to learn the spatio-temporal relationships between features, capture individual seizure propagation patterns, and perform seizure onset detection in a heterogeneous multi-patient dataset. Evaluation on a real-world dataset demonstrates that {VISOR} outperforms state-of-the-art baselines by at least 5\\% points for seizure onset detection in terms of the F1 score and indicates higher effectiveness for more complex patterns of propagating seizures.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The onset detection of epileptic seizures from multivariate Electroencephalogram ({EEG}) data is a challenging task. The variation in seizure patterns across patients and epilepsy types makes it particularly difficult to create a generic solution. Existing approaches indicate low recall due to their inability to capture complex seizure onset patterns. In this paper, we propose {VISOR} \u2013 a novel approach to detect the onset of epileptic seizures based on novel patient [&hellip;]<\/p>\n","protected":false},"author":12,"featured_media":0,"template":"","meta":{"_acf_changed":false,"footnotes":""},"publication-type":[32],"class_list":["post-32374","publication","type-publication","status-publish","hentry","publication-type-inproceedings"],"acf":[],"publishpress_future_workflow_manual_trigger":{"enabledWorkflows":[]},"_links":{"self":[{"href":"https:\/\/lamarr-institute.org\/de\/wp-json\/wp\/v2\/publication\/32374","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lamarr-institute.org\/de\/wp-json\/wp\/v2\/publication"}],"about":[{"href":"https:\/\/lamarr-institute.org\/de\/wp-json\/wp\/v2\/types\/publication"}],"author":[{"embeddable":true,"href":"https:\/\/lamarr-institute.org\/de\/wp-json\/wp\/v2\/users\/12"}],"version-history":[{"count":0,"href":"https:\/\/lamarr-institute.org\/de\/wp-json\/wp\/v2\/publication\/32374\/revisions"}],"wp:attachment":[{"href":"https:\/\/lamarr-institute.org\/de\/wp-json\/wp\/v2\/media?parent=32374"}],"wp:term":[{"taxonomy":"publication-type","embeddable":true,"href":"https:\/\/lamarr-institute.org\/de\/wp-json\/wp\/v2\/publication-type?post=32374"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}