About: A procedure for decomposing the myoelectric signal into its constituent action potentials--Part I: Technique, theory, and implementation

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scientific article published on 01 March 1982

Attributes	Values
rdf:type	Item
description	wetenschappelijk artikel (nl) наукова стаття, опублікована в березні 1982 (uk) im März 1982 veröffentlichter wissenschaftlicher Artikel (de) artículu científicu espublizáu en marzu de 1982 (ast) scientific article published on 01 March 1982 (en)
publication date	wds:Q70371507-E6CAEA89-35EA-4211-B860-481668152AD3
publication date	1982-03-01 00:00:00Z (xsd:dateTime)
author name string	wds:Q70371507-CA863C19-AAD6-4A35-A4E4-1A24128ADD92 wds:Q70371507-EB06A109-F248-49D4-8D35-448C991EDF09
author name string	C J De Luca R S LeFever
rdfs:label	A procedure for decomposing the myoelectric signal into its constituent action potentials--Part I: Technique, theory, and implementation (en) A procedure for decomposing the myoelectric signal into its constituent action potentials--Part I: Technique, theory, and implementation (nl)
skos:prefLabel	A procedure for decomposing the myoelectric signal into its constituent action potentials--Part I: Technique, theory, and implementation (en) A procedure for decomposing the myoelectric signal into its constituent action potentials--Part I: Technique, theory, and implementation (nl)
name	A procedure for decomposing the myoelectric signal into its constituent action potentials--Part I: Technique, theory, and implementation (en) A procedure for decomposing the myoelectric signal into its constituent action potentials--Part I: Technique, theory, and implementation (nl)
title	wds:Q70371507-241DBFC5-FF60-43EC-A4D5-6A049B182D85
title	A procedure for decomposing the myoelectric signal into its constituent action potentials--Part I: Technique, theory, and implementation (en)
page(s)	wds:Q70371507-78A49F47-8076-4CE3-9385-063AF59E8FD7
page(s)	149-157
instance of	wds:Q70371507-B9B5CBED-7307-4C95-AEFA-E4E19786D344
instance of	scholarly article
PubMed ID	wds:Q70371507-A2DB60B8-4305-4A26-9E8D-E3142D096AA7
PubMed ID	http://rdf.ncbi.nlm.nih.gov/pubchem/reference/7084948
PubMed ID	7084948
published in	wds:Q70371507-B5A44A3B-E4A5-45ED-B2B3-CEEB0430CF3B
published in	IEEE Transactions on Biomedical Engineering
issue	wds:Q70371507-10505935-0468-4C2B-85A9-AA297176CBB3
volume	wds:Q70371507-12A61026-5932-44E5-B9A1-A595DC909BAE
issue	3
volume	29
DOI	wds:Q70371507-8D54A8CF-E7B4-4601-BEF1-E555C6CD78A3
DOI	http://dx.doi.org/10.1109/TBME.1982.324881
DOI	10.1109/TBME.1982.324881
is about of	https://www.wikidata.org/wiki/Special:EntityData/Q70371507
is cites work of	Behaviour of human motor units in different muscles during linearly varying contractions Automatic identification of motor unit action potential trains from electromyographic signals using fuzzy techniques. Motor unit control and force fluctuation during fatigue High-yield decomposition of surface EMG signals Error reduction in EMG signal decomposition Assessment of validity of a high-yield surface electromyogram decomposition. Assessment of single motor unit conduction velocity during sustained contractions of the tibialis anterior muscle with advanced spike triggered averaging. New signal processing techniques for the decomposition of EMG signals Spike sorting by stochastic simulation EMG signal decomposition: how can it be accomplished and used? Robust supervised classification of motor unit action potentials. The influence of contraction amplitude and firing history on spike-triggered averaged trapezius motor unit potentials. Robust method for estimating motor unit firing-pattern statistics. Spike train analysis. Sex differences in rabbit masseter motoneuron firing behavior Hierarchical control of motor units in voluntary contractions MUAP extraction and classification based on wavelet transform and ICA for EMG decomposition. Rigorous a posteriori assessment of accuracy in EMG decomposition Decomposition of indwelling EMG signals Recruitment Order of Motor Units in Human Vastus Lateralis Muscle Is Maintained During Fatiguing Contractions Evaluation of intra-muscular EMG signal decomposition algorithms. A technique for the detection, decomposition and analysis of the EMG signal Control scheme governing concurrently active human motor units during voluntary contractions Equalization filters for multiple-channel electromyogram arrays Multielectrode surface EMG for noninvasive estimation of motor unit size. Magnetic stimulation-induced modulations of motor unit firings extracted from multi-channel surface EMG. Synchronization of motor unit firings: an epiphenomenon of firing rate characteristics not common inputs Motor unit recruitment and proprioceptive feedback decrease the common drive Respiratory and stress-induced activation of low-threshold motor units in the human trapezius muscle. Preferred sensor sites for surface EMG signal decomposition Resolving superimposed MUAPs using particle swarm optimization Comparative Analysis of Wavelet-based Feature Extraction for Intramuscular EMG Signal Decomposition. Resolving superimposed motor unit action potentials. Relationship between firing rate and recruitment threshold of motoneurons in voluntary isometric contractions Adaptive motor unit action potential clustering using shape and temporal information. A Novel Framework Based on FastICA for High Density Surface EMG Decomposition The recruitment pattern of single vasoconstrictor neurons in human. Do metabolites that are produced during resistance exercise enhance muscle hypertrophy? Surface EMG decomposition based on K-means clustering and convolution kernel compensation Firing patterns of low-threshold trapezius motor units in feedback-controlled contractions and vocational motor activities. EMG-force relation in dynamically contracting cat plantaris muscle. Digital filter design for peak detection of surface EMG. Decomposition of surface EMG signals from cyclic dynamic contractions Challenges in computerized MUAP analysis Introduction to this special issue. Intelligent data analysis in electromyography and electroneurography New approaches to motor unit potential analysis A simulation study for a surface EMG sensor that detects distinguishable motor unit action potentials Modelling myoelectric interference patterns during movement Validating motor unit firing patterns extracted by EMG signal decomposition. Intramuscular EMG Decomposition Basing on Motor Unit Action Potentials Detection and Superposition Resolution. Long-Term High-Density Extracellular Recordings Enable Studies of Muscle Cell Physiology [Signal processing in electromyography: a review] Model for decomposition of the motor unit action potential. 1. The algorithm Motor unit drive: a neural interface for real-time upper limb prosthetic control Muscle fiber conduction velocity estimation by using normalized peak-averaging technique
is cites work of	wds:Q36846766-DD8F9FF7-541E-487C-B870-4AD8E7435B82 wds:Q36212371-661F3209-F8C3-4886-BFFF-3231EAA53C60 wds:Q36013277-11152786-1AE7-4DD9-93FB-F18B07234B13 wds:Q52076716-4E3EEFCE-1200-490B-91F5-8906AD69DBDD wds:Q47552848-126920D9-2341-4869-AD92-36A2F4A17ACD wds:Q51140024-56408D49-286A-46CD-A977-98CC1277B400 wds:Q70518052-AAE28C2D-3596-4BDE-AA15-FDE078716D50 wds:Q34627109-E3EC71A2-DCC9-4F87-B99D-8C5C07FC3B9A

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