TactileNet is a model based on deep learning that employs the convolutional neural network to classify tactile EEG data as input. The contemporary state-of-the-art TactileNet is inspired by models like EEGNet(https://github.com/vlawhern/arl-eegmodels), Inception, and SENet(https://github.com/hujie-frank/SENet). For more information about the model follow the link below: https://doi.org/10.1109/ICEE55646.2022.9827406
If you are using this code please cite our paper.
@inproceedings{amini2022surface,
title={Surface roughness classification in dynamic touch using EEG signals},
author={Amini, Ali and Faez, Karim and Amiri, Mahmood},
booktitle={2022 30th International Conference on Electrical Engineering (ICEE)},
pages={205--209},
year={2022},
organization={IEEE}
}
Full text is also available: https://www.researchgate.net/publication/362147873_Surface_roughness_classification_in_dynamic_touch_using_EEG_signals