ArticleFrontiers in neurology2021
Forecasting Seizure Likelihood With Wearable Technology.
Article in Frontiers in neurology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 3 of them syntheses that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
40 citing papers in PubMed, 3 syntheses or guidelines pooled it, 92 citations in OpenAlex.
- Movement Disorders and Smart Wrist Devices: A Comprehensive Study.Sensors (Basel, Switzerland) · 2025Pooled it
- Automated algorithms for seizure forecast: a systematic review and meta-analysis.Journal of neurology · 2024Pooled it
- Feasibility of cardiac-based seizure detection and prediction: A systematic review of non-invasive wearable sensor-based studies.Epilepsia open · 2024Pooled it
- Article
- Timing is everything: Expert opinion on researching epilepsy rhythms by the ILAE Task Force on Chronobiology.Epilepsia · 2026Review
- Neurobehavioral Signatures of Epileptogenesis: Molecular Programs, Trait-like Phenotypes, and Translational Biomarkers Beyond Seizures.International journal of molecular sciences · 2026Review
- The research progress of wearable digital health technologies in epilepsy management.Acta epileptologica · 2026Review
- Investigation of stress hormones across multiday seizure cycles.Brain communications · 2026Article
- EPIStress: A multimodal dataset of Physiological signals to measure cognitive stress in epilepsy patients.Scientific data · 2025Article
- Real-world epilepsy monitoring with ultra-long-term subcutaneous electroencephalography: A 15-month prospective study.Epilepsia · 2025Observational
- Wearable Artificial Intelligence for Epilepsy: Scoping Review.Journal of medical Internet research · 2025Article
- Rhythms in Longitudinal Thalamic Recordings are Linked to Seizure Risk.medRxiv : the preprint server for health sciences · 2025Article
- Article
- Forecasting epileptic seizures with wearable devices: A hybrid short- and long-horizon pseudo-prospective approach.Epilepsia · 2025Article
- Autonomic biosignals, seizure detection, and forecasting.Epilepsia · 2025Review
- Article
- Dynamic multiday seizure cycles and evolving rhythms in a tetanus toxin rat model of epilepsy.Scientific reports · 2025Article
- ECG-based epileptic seizure prediction: Challenges of current data-driven models.Epilepsia open · 2025Article
- Cycles in seizure duration and their underlying dynamics in the tetanus toxin rat model.Brain communications · 2025Article
- Epileptic seizure forecasting with wearable-based nocturnal sleep features.Epilepsia open · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 6 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The unpredictability of epileptic seizures exposes people with epilepsy to potential physical harm, restricts day-to-day activities, and impacts mental well-being. Accurate seizure forecasters would reduce the uncertainty associated with seizures but need to be feasible and accessible in the long-term. Wearable devices are perfect candidates to develop non-invasive, accessible forecasts but are yet to be investigated in long-term studies. We hypothesized that machine learning models could utilize heart rate as a biomarker for well-established cycles of seizures and epileptic activity, in addition to other wearable signals, to forecast high and low risk seizure periods. This feasibility study tracked participants' (
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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.