Hand Movement Classification Using Burg Reflection Coefficients

Hand Movement Classification Using Burg Reflection Coefficients

Classification of electromyographic signals has a wide range of applications, from clinical diagnosis of different muscular diseases to biomedical engineering, where their use as input for the control of prosthetic devices has become a hot topic of research. The challenge of classifying these signal...

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Bibliographic Details
Main Authors: Daniel Ramírez-Martínez, Mariel Alfaro-Ponce, Oleksiy Pogrebnyak, Mario Aldape-Pérez, Amadeo-José Argüelles-Cruz
Format: Article
Language:English
Published: MDPI AG 2019-01-01
Series:Sensors
Subjects:
electromyography
hand movement
health monitoring
maximum entropy reflection coefficients
classification algorithms
machine learning
feature selection
Online Access:https://www.mdpi.com/1424-8220/19/3/475

Internet

https://www.mdpi.com/1424-8220/19/3/475

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