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 language | English |
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Title of host publication | ICASSP, the International Conference on Acoustics, Speech, and Signal Processing 2023 |
Publisher | IEEE - Institute of Electrical and Electronics Engineers Inc. |
Publication status | Published - 2023 |
Event | IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2023) - Rhodes Island, Greece Duration: 2023 Jun 4 → 2023 Jun 10 |
Conference
Conference | IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2023) |
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Country/Territory | Greece |
City | Rhodes Island |
Period | 2023/06/04 → 2023/06/10 |
Subject classification (UKÄ)
- Biomedical Laboratory Science/Technology