Towards Interpretable Seizure Detection Using Wearables
2023-05-05IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2023Code Available0· sign in to hype
Irfan Al-Hussaini, Cassie S. Mitchell
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Abstract
Seizure detection using machine learning is a critical problem for the timely intervention and management of epilepsy. We propose SeizFt, a robust seizure detection framework using EEG from a wearable device. It uses features paired with an ensemble of trees, thus enabling further interpretation of the model’s results. The efficacy of the underlying augmentation and class-balancing strategy is also demonstrated. This study was performed for the Seizure Detection Challenge 2023, an ICASSP Grand Challenge.