sEMG-angle estimation using feature engineering techniques for least square support vector machine

In the practical implementation of control of electromyography (sEMG) driven devices, algorithms should recognize the human’s motion from sEMG with fast speed and high accuracy. This study proposes two feature engineering (FE) techniques, namely, feature-vector resampling and time-lag techniques, to...

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Detalles Bibliográficos
Autores principales: Gao, Yongsheng, Luo, Yang, Zhao, Jie, Li, Qiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: IOS Press 2019
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6598017/
https://www.ncbi.nlm.nih.gov/pubmed/31045525
http://dx.doi.org/10.3233/THC-199005

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6598017/
https://www.ncbi.nlm.nih.gov/pubmed/31045525
http://dx.doi.org/10.3233/THC-199005

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