Towards Interpretable Seizure Detection Using Wearables

Irfan Al-Hussaini; Cassie S. Mitchell

ICASSP 2023accepted0 citations

Towards Interpretable Seizure Detection Using Wearables

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.

BibTeX

@inproceedings{icassp2023_towardsinterpret,
  title = {Towards Interpretable Seizure Detection Using Wearables},
  author = {Irfan Al-Hussaini and Cassie S. Mitchell},
  booktitle = {ICASSP 2023},
  year = {2023}
}