Detection of nocturnal epileptic seizures using a wearable armband: A deep learning approach combining accelerometry and photoplethysmography signals

Our two-step approach enables accurate, long-term detection of severe nocturnal seizures in home settings. The wearable system provides a practical solution for continuous monitoring and real-time alerts, thus potentially reducing SUDEP risk and improving patient safety, fulfilling an urgent unmet need in epilepsy care. Furthermore, by enabling long-term home monitoring, this system may help assess the relationship between seizure events and lifestyle-related triggers such as sleep deprivation, stress, physical exertion, or alcohol consumption, thereby supporting the development of personalized preventive strategies.

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Publication Details

Journal
Computer Methods and Programs in Biomedicine
Published
2025-09-29
DOI
https://doi.org/10.1016/j.cmpb.2025.109087
Citations
1
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
1.43

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article

Detection of nocturnal epileptic seizures using a wearable armband: A deep learning approach combining accelerometry and photoplethysmography signals

Chunjiao Dong, Ronald M. Aarts, Xi Long, Johannes van Dijk et al.
1 citations
Computer Methods and Programs in Biomedicine
EEG and Brain-Computer Interfaces
1.43
article

Detection of nocturnal epileptic seizures using a wearable armband: A deep learning approach combining accelerometry and photoplethysmography signals

Chunjiao Dong, Ronald M. Aarts, Xi Long, Johannes van Dijk, Yunfeng Wang
article en
1 citations

Abstract

Our two-step approach enables accurate, long-term detection of severe nocturnal seizures in home settings. The wearable system provides a practical solution for continuous monitoring and real-time alerts, thus potentially reducing SUDEP risk and improving patient safety, fulfilling an urgent unmet need in epilepsy care. Furthermore, by enabling long-term home monitoring, this system may help assess the relationship between seizure events and lifestyle-related triggers such as sleep deprivation, stress, physical exertion, or alcohol consumption, thereby supporting the development of personalized preventive strategies.

Computer Methods and Programs in BiomedicineVol. 273
Hebei Medical University (CN), Institute of Microelectronics (SG), Institute of Microelectronics (CN), Kempenhaeghe (NL), Eindhoven University of Technology (NL)
Hebei Provincial Department of Human Resources and Social Security, Hebei Medical University
Openalex Percentile: Top 15%
EEG and Brain-Computer Interfaces
1.43
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