scholarly journals Motor Unit Potential Train Validation and Its Application in EMG Signal Decomposition

10.5772/37561 ◽  
2012 ◽  
Author(s):  
Hossein Parsaei ◽  
Daniel W.
Keyword(s):  
Motor Unit ◽  
Signal Decomposition ◽  
Motor Unit Potential ◽  
Emg Signal Decomposition ◽  
Emg Signal ◽  
Motor Unit Potential Train

scholarly journals A MATLAB-Based Interactive Environment for EMG Signal Decomposition Utilizing Matched Template Filters

2015 ◽  
Vol 4 (3) ◽  
pp. 189-204
Author(s):  
Sarbast Rasheed
Keyword(s):  
Motor Unit ◽  
User Interfaces ◽  
Software Package ◽  
Signal Decomposition ◽  
Motor Unit Potential ◽  
Interactive Software ◽  
Emg Signal Decomposition ◽  
Emg Signal ◽  
Interactive Environment ◽  
Pattern Information

An interactive software package for analyzing and decomposing electromyographic (EMG) signals is designed, constructed, and implemented using the MATLAB high-level programming language and its interactive environment. EMG signal analysis in the form of signal decomposition into their constituent motor unit potential trains (MUPTs) is considered as a classification task. Matched template filter methods have been employed for the classification of motor unit potentials (MUPs) in which the assignment criterion used for MUPs is based on a combination of MUP shapes and motor unit firing pattern information. The developed software package consists of several graphical user interfaces used to detect individual MUP waveforms from raw EMG signals, extract relevant features, and classify MUPs into MUPTs using matched template filter classifiers. The proposed software package is useful for enhancing the analysis quality and providing a systematic approach to the EMG signal decomposition process. It also worked as a very helpful environment for testing and evaluating algorithms developed for EMG signal decomposition research.

Cross Comparison of Motor Unit Potential Features Used in EMG Signal Decomposition

2018 ◽  
Vol 26 (5) ◽  
pp. 1017-1025 ◽  
Author(s):  
Mohsen Ghofrani Jahromi ◽  
Hossein Parsaei ◽  
Ali Zamani ◽  
Daniel W. Stashuk
Keyword(s):  
Motor Unit ◽  
Signal Decomposition ◽  
Motor Unit Potential ◽  
Emg Signal Decomposition ◽  
Emg Signal

Validating motor unit firing patterns extracted by EMG signal decomposition

2010 ◽  
Vol 49 (6) ◽  
pp. 649-658 ◽  
Author(s):  
Hossein Parsaei ◽  
Faezeh Jahanmiri Nezhad ◽  
Daniel W. Stashuk ◽  
Andrew Hamilton-Wright
Keyword(s):  
Motor Unit ◽  
Signal Decomposition ◽  
Firing Patterns ◽  
Emg Signal Decomposition ◽  
Emg Signal ◽  
Motor Unit Firing

Analysis of intramuscular electromyogram signals

2008 ◽  
Vol 367 (1887) ◽  
pp. 357-368 ◽  
Author(s):  
Roberto Merletti ◽  
Dario Farina
Keyword(s):  
Motor Unit ◽  
Action Potentials ◽  
Signal Decomposition ◽  
Human Interaction ◽  
Emg Signal Decomposition ◽  
Emg Signal ◽  
Motor Unit Action Potentials ◽  
Motor Unit Action ◽  
Unit Action ◽  
Individual Motor

Intramuscular electromyographic (EMG) signals are detected with needles or wires inserted into muscles. With respect to non-invasive techniques, intramuscular electromyography has high selectivity for individual motor unit action potentials and is thus used to measure motor unit activity. Decomposition of intramuscular signals into individual motor unit action potentials consists in detection and classification, usually followed by separation of superimposed action potentials. Although intramuscular EMG signal decomposition is the primary tool for physiological investigations of motor unit properties, it is rarely applied in clinical routine, because of the need for human interaction and the difficulty in interpreting the quantitative data provided by EMG signal decomposition to support clinical decisions. The current clinical use of intramuscular EMG signals relates to the diagnosis of myopathies, of diseases of the α-motor neuron and of the neuromuscular junction through the analysis of the interference signal or of the shape of some motor unit action potentials, usually without a full decomposition of the signal.

scholarly journals Preferred sensor sites for surface EMG signal decomposition

2012 ◽  
Vol 33 (2) ◽  
pp. 195-206 ◽  
Author(s):  
Farah Zaheer ◽  
Serge H Roy ◽  
Carlo J De Luca
Keyword(s):  
Surface Emg ◽  
Signal Decomposition ◽  
Emg Signal Decomposition ◽  
Emg Signal ◽  
Surface Emg Signal
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