EMG signal decomposition: how can it be accomplished and used?
about
Alternative communication systems for people with severe motor disabilities: a survey.Recruitment in retractor bulbi muscle during eyeblink conditioning: EMG analysis and common-drive modelBayesian aggregation versus majority vote in the characterization of non-specific arm pain based on quantitative needle electromyographyAutomatic classification of motor unit potentials in surface EMG recorded from thenar muscles paralyzed by spinal cord injury.Assessing motor deficits in compressive neuropathy using quantitative electromyography.High-yield decomposition of surface EMG signals.Decoding subtle forearm flexions using fractal features of surface electromyogram from single and multiple sensors.Spike sorting paradigm for classification of multi-channel recorded fasciculation potentials.Behaviour of motor unit action potential rate, estimated from surface EMG, as a measure of muscle activation level.Examination of Poststroke Alteration in Motor Unit Firing Behavior Using High-Density Surface EMG Decomposition.Equalization filters for multiple-channel electromyogram arrays.Motor unit potential morphology differences in individuals with non-specific arm pain and lateral epicondylitis.Resolving superimposed MUAPs using particle swarm optimizationProgressive FastICA Peel-Off and Convolution Kernel Compensation Demonstrate High Agreement for High Density Surface EMG DecompositionAnalysis of intramuscular electromyogram signals.Applications of ICA and fractal dimension in sEMG signal processing for subtle movement analysis: a review.A hybrid classifier for characterizing motor unit action potentials in diagnosing neuromuscular disorders.Surface EMG decomposition based on K-means clustering and convolution kernel compensation.Validating motor unit firing patterns extracted by EMG signal decomposition.Comparative Analysis of Wavelet-based Feature Extraction for Intramuscular EMG Signal Decomposition.Intramuscular EMG Decomposition Basing on Motor Unit Action Potentials Detection and Superposition Resolution.Evidence from retractor bulbi EMG for linearized motor control of conditioned nictitating membrane responses.Feature selection for motor unit potential train characterization.Fluctuations in isometric muscle force can be described by one linear projection of low-frequency components of motor unit discharge rates.Long-Term High-Density Extracellular Recordings Enable Studies of Muscle Cell Physiology
P2860
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P2860
EMG signal decomposition: how can it be accomplished and used?
description
2001 nî lūn-bûn
@nan
2001 թուականի Յունիսին հրատարակուած գիտական յօդուած
@hyw
2001 թվականի հունիսին հրատարակված գիտական հոդված
@hy
2001年の論文
@ja
2001年論文
@yue
2001年論文
@zh-hant
2001年論文
@zh-hk
2001年論文
@zh-mo
2001年論文
@zh-tw
2001年论文
@wuu
name
EMG signal decomposition: how can it be accomplished and used?
@ast
EMG signal decomposition: how can it be accomplished and used?
@en
EMG signal decomposition: how can it be accomplished and used?
@nl
type
label
EMG signal decomposition: how can it be accomplished and used?
@ast
EMG signal decomposition: how can it be accomplished and used?
@en
EMG signal decomposition: how can it be accomplished and used?
@nl
prefLabel
EMG signal decomposition: how can it be accomplished and used?
@ast
EMG signal decomposition: how can it be accomplished and used?
@en
EMG signal decomposition: how can it be accomplished and used?
@nl
P1476
EMG signal decomposition: how can it be accomplished and used?
@en
P2093
P304
P356
10.1016/S1050-6411(00)00050-X
P577
2001-06-01T00:00:00Z