SlimSeiz: Efficient Channel-Adaptive Seizure Prediction Using a Mamba-Enhanced Network

IEEE International Symposium on Circuits and Systems proceedings, pp. 1–5

Abstract

Epileptic seizures cause abnormal brain activity, and their unpredictability can lead to accidents, underscoring the need for long-term seizure prediction. Although seizures can be predicted by analyzing electroencephalogram (EEG) signals, existing methods often require too many channels or larger models, limiting mobile usability. This paper introduces a SlimSeiz framework that utilizes adaptive channel selection with a lightweight neural network model. SlimSeiz operates in two states: the first stage selects the optimal channel set for seizure prediction using machine learning algorithms, and the second stage employs a lightweight neural network based on convolution and Mamba for prediction. On the Children’s Hospital Boston-MIT (CHB-MIT) EEG dataset, SlimSeiz can reduce channels from 22 to 8 while claiming a satisfactory result of 94.8% accuracy, 95.5% sensitivity, and 94.0% specificity with only 21.2 K model parameters, matching or outperforming larger models’ performance. We also validate SlimSeiz on a new EEG dataset, SRH-LEI, collected from Shanghai Renji Hospital, demonstrating its effectiveness across different patients. The code and SRH-LEI dataset are available at https://github.com/guoruilu/SlimSeiz.

Authors 6

1. Jing Peng

   Shanghai Jiao Tong University · Renji Hospital

   Affiliation as printed

   Shanghai Jiao Tong University,Renji Hospital, School of Medicine,Shanghai,China

2. Bingyuan Huang

   Shanghai Jiao Tong University · Renji Hospital

   Affiliation as printed

   Shanghai Jiao Tong University,Renji Hospital, School of Medicine,Shanghai,China

3. Chang Gao

   Delft University of Technology

   Affiliation as printed

   Delft University of Technology,Department of Microelectronics,The Netherlands

4. Todor P. Stefanov Aachen Leiden Institute of Advanced Computer Science

   Leiden University

   Affiliation as printed

   Leiden University,Leiden Institute of Advanced Computer Science (LIACS),The Netherlands

5. Yong Hao

   Shanghai Jiao Tong University · Renji Hospital

   Affiliation as printed

   Shanghai Jiao Tong University,Renji Hospital, School of Medicine,Shanghai,China

6. Qinyu Chen Aachen Leiden Institute of Advanced Computer Science

   Leiden University

   Affiliation as printed

   Leiden University,Leiden Institute of Advanced Computer Science (LIACS),The Netherlands