Lightweight Machine Learning for Seizure Detection on Wearable Devices

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Abstract

For patients with epilepsy, automatic epilepsy monitoring, i.e., the process of direct observation of the patient’s health status in real time, is crucial. Wearable systems provide the possibility of real-time epilepsy monitoring and alerting caregivers upon the occurrence of a seizure. In the context of the ICASSP 2023 Seizure Detection Challenge, we pro- pose a lightweight machine-learning framework for real-time epilepsy monitoring on wearable devices. We evaluate our proposed framework on the SeizeIT2 dataset from the wear- able SensorDot (SD) of Byteflies. The experimental results show that our proposed framework achieves a sensitivity of 73.6% and a specificity of 96.7% in seizure detection.
Original languageEnglish
Title of host publicationICASSP, the International Conference on Acoustics, Speech, and Signal Processing 2023
PublisherIEEE - Institute of Electrical and Electronics Engineers Inc.
Publication statusPublished - 2023
EventIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2023) - Rhodes Island, Greece
Duration: 2023 Jun 42023 Jun 10

Conference

ConferenceIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2023)
Country/TerritoryGreece
CityRhodes Island
Period2023/06/042023/06/10

Subject classification (UKÄ)

  • Biomedical Laboratory Science/Technology

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