DSN : Energy-efficient EMG signal classification method enabling real-time monitoring for edge healthcare.
- DOI
- 10.1016/j.neunet.2026.109306
- Published
- 2027 Jan
- Container
- Neural networks : the official journal of the International Neural Network Society
- Publisher
- Not recorded
- Open access
- unknown
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limited evidence Score 43/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.1016/j.neunet.2026.109306,
title = {DSN : Energy-efficient EMG signal classification method enabling real-time monitoring for edge healthcare.},
author = {Zhang Z and Meng X and Wei J and Zeng M and Zeng Z},
year = {2027},
journal = {Neural networks : the official journal of the International Neural Network Society},
doi = {10.1016/j.neunet.2026.109306},
url = {https://doi.org/10.1016/j.neunet.2026.109306}
}RIS
TY - JOUR TI - DSN : Energy-efficient EMG signal classification method enabling real-time monitoring for edge healthcare. AU - Zhang Z AU - Meng X AU - Wei J AU - Zeng M AU - Zeng Z PY - 2027 JO - Neural networks : the official journal of the International Neural Network Society DO - 10.1016/j.neunet.2026.109306 UR - https://doi.org/10.1016/j.neunet.2026.109306 ER -
APA
Z, Z., X, M., J, W., M, Z., & Z, Z. (2027). DSN : Energy-efficient EMG signal classification method enabling real-time monitoring for edge healthcare.. Neural networks : the official journal of the International Neural Network Society. https://doi.org/10.1016/j.neunet.2026.109306
Source records
- pubmed · retrieved 2026-09-26T02:43:52.627Z