Cargando…
Mechanomyography Signal Pattern Recognition of Knee and Ankle Movements Using Swarm Intelligence Algorithm-Based Feature Selection Methods
Pattern recognition of lower-limb movements based on mechanomyography (MMG) signals has a certain application value in the study of wearable rehabilitation-training devices. In this paper, MMG feature selection methods based on a chameleon swarm algorithm (CSA) and a grasshopper optimization algorit...
Autores principales: | Zhang, Yue, Sun, Maoxun, Xia, Chunming, Zhou, Jie, Cao, Gangsheng, Wu, Qing |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10422262/ https://www.ncbi.nlm.nih.gov/pubmed/37571722 http://dx.doi.org/10.3390/s23156939 |
Ejemplares similares
-
Research on GA-SVM Based Head-Motion Classification via Mechanomyography Feature Analysis
por: Zhang, Yue, et al.
Publicado: (2019) -
Evolutionary and swarm intelligence algorithms
por: Bansal, Jagdish Chand, et al.
Publicado: (2018) -
Estimation of Electrically-Evoked Knee Torque from Mechanomyography Using Support Vector Regression
por: Ibitoye, Morufu Olusola, et al.
Publicado: (2016) -
Estimation of Knee Extension Force Using Mechanomyography Signals Based on GRA and ICS-SVR
por: Li, Zebin, et al.
Publicado: (2022) -
Mechanomyography versus Electromyography, in monitoring the muscular fatigue
por: Tarata, Mihai T
Publicado: (2003)