Advances in clinical neurorestorative treatments of Parkinson’s disease DOI Creative Commons

Yixuan Yin,

Dongning Su,

Joyce S. T. Lam

et al.

Journal of Neurorestoratology, Journal Year: 2025, Volume and Issue: unknown, P. 100204 - 100204

Published: March 1, 2025

Language: Английский

Brain-Computer Interface (BCI) in clinical neurorestorative practices DOI Creative Commons
Yunfa Fu, Y. Y. Xue, Xiaogang Chen

et al.

Journal of Neurorestoratology, Journal Year: 2025, Volume and Issue: unknown, P. 100188 - 100188

Published: Jan. 1, 2025

Citations

0
DSTA-Net: Dynamic Spatio-Temporal Feature Augmentation Network for Motor Imagery Classification DOI Creative Commons
Liang Chang, Banghua Yang, Jun Zhang

et al.

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: March 18, 2025

Abstract Accurate decoding and strong feature interpretability of Motor Imagery (MI) are expected to drive MI applications in stroke rehabilitation. However, the inherent nonstationarity high intra-class variability MI-EEG pose significant challenges extracting reliable spatio-temporal features. We proposed Dynamic Spatio-Temporal Feature Augmentation Network (DSTA-Net), which combines DSTA Convolution (STC) modules. In module, multi-scale temporal convolutional kernels tailored α β frequency bands neurophysiological characteristics, while raw EEG serve as a baseline layer retain original information. Next, Grouped Spatial Convolutions extract multi-level spatial features, combined with weight constraints prevent overfitting. convolution map channel information into new domain, enabling further extraction through dimensional transformation. And STC module extracts features conducts classification. evaluated DSTA-Net on three public datasets applied it self-collected dataset. 10-fold cross-validation, achieved average accuracy improvements 6.29% (p<0.01), 3.05% 5.26%(p<0.01), 2.25% over ShallowConvNet BCI-IV-2a, OpenBMI, CASIA, dataset, respectively. hold-out validation, 3.99% (p<0.01) 4.2% OpenBMI CASIA datasets, Finally, we DeepLIFT, Common Pattern, t-SNE analyze contributions individual channels, patterns, visualize The superiority offers insights for research application MI. code is available https://github.com/CL-Cloud-BCI/DSTANet-code.

Language: Английский

Citations

0
Advances in clinical neurorestorative treatments of Parkinson’s disease DOI Creative Commons

Yixuan Yin,

Dongning Su,

Joyce S. T. Lam

et al.

Journal of Neurorestoratology, Journal Year: 2025, Volume and Issue: unknown, P. 100204 - 100204

Published: March 1, 2025

Language: Английский

Citations

0