ArticleScientific data2025
SeizeIT2: Wearable Dataset Of Patients With Focal Epilepsy.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- A multicenter, video-EEG-based validation of a multimodal wearable device for focal seizure detection in adults: The SeizeIT2 study.Epilepsia open · 2026Trial
- An edge-AI enabled wearable platform for real-time epileptic seizure detection with geolocated alerting.BMC biomedical engineering · 2026Article
- CMEpiNet: Complex-Valued Multimodal Epilepsy Detection Network Model.Sensors (Basel, Switzerland) · 2026Article
- Seizure burden and treatment efficacy evaluation in anti-LGI1 autoimmune encephalitis patients using wearable device: a pilot feasibility study.BMJ neurology open · 2026Article
- ECG-Based Detection of Epileptic Seizures in Real-World Wearable Settings: Insights from the SeizeIT2 Dataset.Sensors (Basel, Switzerland) · 2025Article
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Authors and funding
13 authors.
Funding
Abstract
The increasing technological advancements towards miniaturized physiological measuring devices have enabled continuous monitoring of epileptic patients outside of specialized environments. The large amounts of data that can be recorded with such devices hold significant potential for developing automated seizure detection frameworks. In this work, we present SeizeIT2, the first open dataset of wearable data recorded in patients with focal epilepsy. The dataset comprises more than 11,000 hours of multimodal data, including behind-the-ear electroencephalography, electrocardiography, electromyography and movement (accelerometer and gyroscope) data. The dataset contains 883 focal seizures recorded from 125 patients across five different European Epileptic Monitoring Centers. We present a suggestive training/validation split to propel the development of AI methodologies for seizure detection, as well as two benchmark approaches and evaluation metrics. The dataset can be accessed on OpenNeuro and is stored in Brain Imaging Data Structure (BIDS) format.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.