Electromyography Signal Acquisition and Processing for Movement Analysis

This reprint focuses on recent advances in the processing of surface electromyography (EMG) signals acquired during human movement, as well as on innovative approaches to sense muscle activity. A wide range of methods is examined, including machine learning techniques to detect the onset/offset timi...

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Other Authors: Di Nardo, Francesco (Editor), Agostini, Valentina (Editor), Conforto, Silvia (Editor)
Format: Electronic Book Chapter
Language:English
Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2023
Subjects:
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DOAB: description of the publication
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520 |a This reprint focuses on recent advances in the processing of surface electromyography (EMG) signals acquired during human movement, as well as on innovative approaches to sense muscle activity. A wide range of methods is examined, including machine learning techniques to detect the onset/offset timing of muscle activity and approaches to evaluate muscle fatigue and analyze muscle synergies and co-contractions. Applications of these techniques are explored in different medical scenarios, e.g., for the benefit of patients suffering from low back pain, stroke survivors, and patients requiring polysomnography. 
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650 7 |a Technology: general issues  |2 bicssc 
650 7 |a Biotechnology  |2 bicssc 
653 |a gait 
653 |a locomotion 
653 |a motor module 
653 |a number of synergies 
653 |a VAF 
653 |a gait analysis 
653 |a EMG 
653 |a muscle activation patterns 
653 |a movement analysis 
653 |a muscle synergies 
653 |a sEMG 
653 |a stroke 
653 |a factor analysis 
653 |a neurorehabilitation 
653 |a MRC 
653 |a dynamometer 
653 |a strength 
653 |a mechanomyography 
653 |a piezoelectric sensor 
653 |a vibration sensor 
653 |a human-machine interface 
653 |a prosthetic control 
653 |a hand gesture recognition 
653 |a convolutional neural network 
653 |a electromyography 
653 |a polysomnography 
653 |a REM sleep without atonia 
653 |a REM sleep behavior disorder 
653 |a RBD 
653 |a parkinsonism 
653 |a Parkinson's disease 
653 |a spectral power 
653 |a sitting balance 
653 |a trunk control 
653 |a ipsilesional arm 
653 |a MFRT 
653 |a fatiguing frequency-dependent lifting 
653 |a low back pain 
653 |a trunk muscle coactivation 
653 |a onset detection 
653 |a muscle activation 
653 |a machine learning 
653 |a neural networks 
653 |a surface EMG 
653 |a sEMG processing 
653 |a force estimation 
653 |a isometric contractions 
653 |a surface EMG signal 
653 |a co-contraction detection 
653 |a muscular synergies 
653 |a the time-frequency domain 
653 |a wavelet transform 
653 |a power spectral density 
653 |a spectral estimation techniques 
653 |a Welch method 
653 |a Burg method 
653 |a autoregressive model 
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856 4 0 |a www.oapen.org  |u https://directory.doabooks.org/handle/20.500.12854/100037  |7 0  |z DOAB: description of the publication