Deep Learning-Based Epileptic Seizure Detection from EEG and PPG Signals Using LSTM and CNN Models
This study presents a hybrid deep learning framework combining CNNs and LSTMs for automated seizure detection using both EEG and photoplethysmogram (PPG) signals, leveraging complementary physiological information from both modalities. The approach addresses limitations of EEG-only monitoring by incorporating autonomic nervous system markers and heart rate variability changes to improve detection accuracy in subtle or ambiguous seizure cases.
Sources
- MED — Mon Sep 15 2025 00:00:00 GMT+0000 (Coordinated Universal Time) · Read full article (translated)
- MED — Sat Mar 28 2026 00:00:00 GMT+0000 (Coordinated Universal Time) · Read full article (translated)
- MED — Thu Aug 08 2024 00:00:00 GMT+0000 (Coordinated Universal Time) · Read full article (translated)
- MED — Thu Sep 25 2025 00:00:00 GMT+0000 (Coordinated Universal Time) · Read full article (translated)
- MED — Fri Feb 27 2026 00:00:00 GMT+0000 (Coordinated Universal Time) · Read full article (translated)
- MED — Tue Jul 01 2025 00:00:00 GMT+0000 (Coordinated Universal Time) · Read full article (translated)
- MED — Mon Sep 15 2025 00:00:00 GMT+0000 (Coordinated Universal Time) · Read full article (translated)
- PPR — Fri Sep 27 2024 00:00:00 GMT+0000 (Coordinated Universal Time) · Read full article (translated)
- MED — Fri Aug 01 2025 00:00:00 GMT+0000 (Coordinated Universal Time) · Read full article (translated)
- MED — Wed Dec 25 2024 00:00:00 GMT+0000 (Coordinated Universal Time) · Read full article (translated)
Afișăm titlu + rezumat scurt în limita dreptului de autor; textul integral e la sursă.