sEMG-Based Lower Limb Motion Prediction Using CNN-LSTM with Improved PCA Optimization Algorithm

In recent years, sEMG (surface electromyography) signals have been increasingly used to operate wearable devices. The development of mechanical lower limbs or exoskeletons controlled by the nervous system requires greater accuracy in recognizing lower limb activity. There is less research on devices...

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Veröffentlicht in:	Journal of bionics engineering Jg. 20; H. 2; S. 612 - 627
Hauptverfasser:	Zhu, Meng, Guan, Xiaorong, Li, Zhong, He, Long, Wang, Zheng, Cai, Keshu
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Singapore Springer Nature Singapore 01.03.2023 Springer Nature B.V
Schlagworte:	Algorithms Artificial Intelligence Artificial neural networks Back propagation networks Biochemical Engineering Bioinformatics Biomaterials Biomedical Engineering and Bioengineering Biomedical Engineering/Biotechnology Decoding Electromyography Engineering Exoskeleton Exoskeletons Gait Kernel functions Knee Machine learning Myoelectric control Myoelectricity Nervous system Neural networks Predictions Real time Research Article Robot control Signal processing Support vector machines Wearable technology CNN LSTM Exoskeleton sEMG Knee trajectory Bionic robot PCA
ISSN:	1672-6529, 2543-2141
Online-Zugang:	Volltext
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