PhyTransformer: A unified framework for learning spatial–temporal representation from physiological signals-Reference-Cited by-同舟云学术

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PhyTransformer: A unified framework for learning spatial–temporal representation from physiological signals

Published:2025-09 Issue: Volume:189 Page:107578
ISSN:0893-6080
Container-title:Neural Networks
language:en
Short-container-title:Neural Networks

Author:

Li Hongxin^ORCID,Liu Yaru^ORCID,Liu Kun,Qu Yuke,Dai Wei,Tang Jingsheng,Zhou Zongtan

Publisher

Elsevier BV

Reference55 articles.

1. Identification of EMG signals using discriminant analysis and SVM classifier;Alkan;Expert Syst. Appl.,2012

2. An LDA-based approach for real-time simultaneous classification of movements using surface electromyography;Antuvan;IEEE Trans. Neural Syst. Rehabil. Eng.,2019

3. Characterization of a benchmark database for myoelectric movement classification;Atzori;IEEE Trans. Neural Syst. Rehabil. Eng.,2015

4. EEG-ConvTransformer for single-trial EEG-based visual stimulus classification;Bagchi;Pattern Recognit.,2022

5. Multiclass brain–computer interface classification by Riemannian geometry;Barachant;IEEE Trans. Biomed. Eng.,2011

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