It is easy for the electroencephalogram (EEG) signal to be incomplete due to packet loss, electrode falling off, etc. This paper proposed a Cascade Transformer architecture and a loss weighting method for the single-channel EEG completion, which reduced the Normalized Root Mean Square Error (NRMSE) by 2.8% and 8.5%, respectively. With the percentage of the missing points ranging from 1% to 50%, the proposed method achieved a NRMSE from 0.026 to 0.063, which aligned with the state-of-the-art multi-channel completion solution. The proposed work shows it's feasible to perform the EEG completion with only single-channel EEG.
Cite
@article{arxiv.2211.08645,
title = {Single-channel EEG completion using Cascade Transformer},
author = {Chao Zhang and Siqi Han and Milin Zhang},
journal= {arXiv preprint arXiv:2211.08645},
year = {2022}
}
Comments
5 pages, 5 figures, to be published in IEEE Biomedical Circuits and Systems Conference (BioCAS) 2022