Cargando…
SEMG Feature Extraction Based on Stockwell Transform Improves Hand Movement Recognition Accuracy
Feature extraction, as an important method for extracting useful information from surface electromyography (SEMG), can significantly improve pattern recognition accuracy. Time and frequency analysis methods have been widely used for feature extraction, but these methods analyze SEMG signals only fro...
Autores principales: | She, Haotian, Zhu, Jinying, Tian, Ye, Wang, Yanchao, Yokoi, Hiroshi, Huang, Qiang |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6832976/ https://www.ncbi.nlm.nih.gov/pubmed/31615162 http://dx.doi.org/10.3390/s19204457 |
Ejemplares similares
-
A Study on the Classification Effect of sEMG Signals in Different Vibration Environments Based on the LDA Algorithm
por: Wang, Yanchao, et al.
Publicado: (2021) -
Stockwell transform and semi-supervised feature selection from deep features for classification of BCI signals
por: Salimpour, Sahar, et al.
Publicado: (2022) -
Design of an Effective Prosthetic Hand System for Adaptive Grasping with the Control of Myoelectric Pattern Recognition Approach
por: Wang, Yanchao, et al.
Publicado: (2022) -
Application of the Stockwell Transform to Electroencephalographic Signal Analysis during Gait Cycle
por: Ortiz, Mario, et al.
Publicado: (2017) -
Finger knuckle-print authentication using fast discrete orthonormal Stockwell transform
por: Kumar, NB Mahesh, et al.
Publicado: (2017)