Principal Component Analysis Applied to Surface Electromyography: A Comprehensive Review

Principal Component Analysis Applied to Surface Electromyography: A Comprehensive Review

Surface electromyography (sEMG) records muscle activities from the surface of muscles, which offers a wealth of information concerning muscle activation patterns in both research and clinical settings. A key principle underlying sEMG analyses is the decomposition of the signal into a number of motor...

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Bibliographic Details
Main Authors: Ganesh R. Naik, Suviseshamuthu Easter Selvan, Massimiliano Gobbo, Amit Acharyya, Hung T. Nguyen
Format: Article
Language:English
Published: IEEE 2016-01-01
Series:IEEE Access
Subjects:
Surface electromyography (sEMG)
artificial neural network (ANN)
principal component analysis (PCA)
motor unit action potential (MUAP)
flexions
self-organizing feature map (SOFM)
Online Access:https://ieeexplore.ieee.org/document/7516567/

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https://ieeexplore.ieee.org/document/7516567/

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