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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Format: Online
Language:English
Published: MDPI - Multidisciplinary Digital Publishing Institute 2023
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Online Access:ONIX_20230511_9783036572048_54
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collection Directory of Open Access Books
description 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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id doab-20.500.12854ir-100037
institution Directory of Open Access Books
language eng
publishDate 2023
publishDateRange 2023
publishDateSort 2023
publisher MDPI - Multidisciplinary Digital Publishing Institute
publisherStr MDPI - Multidisciplinary Digital Publishing Institute
record_format ojs
spelling doab-20.500.12854ir-1000372024-04-11T15:11:12Z Electromyography Signal Acquisition and Processing for Movement Analysis Di Nardo, Francesco Agostini, Valentina Conforto, Silvia gait locomotion motor module number of synergies VAF gait analysis EMG muscle activation patterns movement analysis muscle synergies sEMG stroke factor analysis neurorehabilitation MRC dynamometer strength mechanomyography piezoelectric sensor vibration sensor human-machine interface prosthetic control hand gesture recognition convolutional neural network electromyography polysomnography REM sleep without atonia REM sleep behavior disorder RBD parkinsonism Parkinson’s disease spectral power sitting balance trunk control ipsilesional arm MFRT fatiguing frequency-dependent lifting low back pain trunk muscle coactivation onset detection muscle activation machine learning neural networks surface EMG sEMG processing force estimation isometric contractions surface EMG signal co-contraction detection muscular synergies the time–frequency domain wavelet transform power spectral density spectral estimation techniques Welch method Burg method autoregressive model thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TC Biochemical engineering::TCB Biotechnology 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. 2023-05-11T17:17:47Z 2023-05-11T17:17:47Z 2023 book ONIX_20230511_9783036572048_54 9783036572048 9783036572055 https://directory.doabooks.org/handle/20.500.12854/100037 eng image/jpeg Attribution 4.0 International https://mdpi.com/books/pdfview/book/7130 https://mdpi.com/books/pdfview/book/7130 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-7205-5 10.3390/books978-3-0365-7205-5 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036572048 9783036572055 202 Basel open access
spellingShingle gait
locomotion
motor module
number of synergies
VAF
gait analysis
EMG
muscle activation patterns
movement analysis
muscle synergies
sEMG
stroke
factor analysis
neurorehabilitation
MRC
dynamometer
strength
mechanomyography
piezoelectric sensor
vibration sensor
human-machine interface
prosthetic control
hand gesture recognition
convolutional neural network
electromyography
polysomnography
REM sleep without atonia
REM sleep behavior disorder
RBD
parkinsonism
Parkinson’s disease
spectral power
sitting balance
trunk control
ipsilesional arm
MFRT
fatiguing frequency-dependent lifting
low back pain
trunk muscle coactivation
onset detection
muscle activation
machine learning
neural networks
surface EMG
sEMG processing
force estimation
isometric contractions
surface EMG signal
co-contraction detection
muscular synergies
the time–frequency domain
wavelet transform
power spectral density
spectral estimation techniques
Welch method
Burg method
autoregressive model
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TC Biochemical engineering::TCB Biotechnology
Electromyography Signal Acquisition and Processing for Movement Analysis
title Electromyography Signal Acquisition and Processing for Movement Analysis
title_full Electromyography Signal Acquisition and Processing for Movement Analysis
title_fullStr Electromyography Signal Acquisition and Processing for Movement Analysis
title_full_unstemmed Electromyography Signal Acquisition and Processing for Movement Analysis
title_short Electromyography Signal Acquisition and Processing for Movement Analysis
title_sort electromyography signal acquisition and processing for movement analysis
topic gait
locomotion
motor module
number of synergies
VAF
gait analysis
EMG
muscle activation patterns
movement analysis
muscle synergies
sEMG
stroke
factor analysis
neurorehabilitation
MRC
dynamometer
strength
mechanomyography
piezoelectric sensor
vibration sensor
human-machine interface
prosthetic control
hand gesture recognition
convolutional neural network
electromyography
polysomnography
REM sleep without atonia
REM sleep behavior disorder
RBD
parkinsonism
Parkinson’s disease
spectral power
sitting balance
trunk control
ipsilesional arm
MFRT
fatiguing frequency-dependent lifting
low back pain
trunk muscle coactivation
onset detection
muscle activation
machine learning
neural networks
surface EMG
sEMG processing
force estimation
isometric contractions
surface EMG signal
co-contraction detection
muscular synergies
the time–frequency domain
wavelet transform
power spectral density
spectral estimation techniques
Welch method
Burg method
autoregressive model
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TC Biochemical engineering::TCB Biotechnology
topic_facet gait
locomotion
motor module
number of synergies
VAF
gait analysis
EMG
muscle activation patterns
movement analysis
muscle synergies
sEMG
stroke
factor analysis
neurorehabilitation
MRC
dynamometer
strength
mechanomyography
piezoelectric sensor
vibration sensor
human-machine interface
prosthetic control
hand gesture recognition
convolutional neural network
electromyography
polysomnography
REM sleep without atonia
REM sleep behavior disorder
RBD
parkinsonism
Parkinson’s disease
spectral power
sitting balance
trunk control
ipsilesional arm
MFRT
fatiguing frequency-dependent lifting
low back pain
trunk muscle coactivation
onset detection
muscle activation
machine learning
neural networks
surface EMG
sEMG processing
force estimation
isometric contractions
surface EMG signal
co-contraction detection
muscular synergies
the time–frequency domain
wavelet transform
power spectral density
spectral estimation techniques
Welch method
Burg method
autoregressive model
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TC Biochemical engineering::TCB Biotechnology
url ONIX_20230511_9783036572048_54