SparseMambaNet: A Novel Architecture Integrating Bi-Mamba and Mixture of Experts for Efficient EEG-Based Lie Detection
Hanbeot Park†1, Yunjeong Cho†1, Hunhee Kim*
- *Correspondence
- †These authors contributed equally to this work.
The code in this repository is currently kept private due to ongoing follow-up research. If you need access for academic purposes, please contact us at the address below, and we will share it upon review. 📧 Contact: [h2kim@pknu.ac.kr]
This repository contains the code for the offline implementation of the EEG-based lie detection methods described in the paper "SparseMambaNet: A Novel Architecture Integrating Bi-Mamba and Mixture of Experts for Efficient EEG-Based Lie Detection". A demo to classify deception from scalp EEG signals during the CQT (Comparison Question Technique) task is provided.