ArticleJournal of applied physiology (Bethesda, Md. : 1985)2008
Decomposition of indwelling EMG signals.
Article in Journal of applied physiology (Bethesda, Md. : 1985), 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
21 citing papers in PubMed.
- Preferred sensor sites for surface EMG signal decomposition.Physiological measurement · 2012Trial
- Motor unit behavior of lumbar multifidus during a forward trunk bending task performed under different speeds and loads in asymptomatic participants.Scientific reports · 2025Article
- Functional force stimulation alters motor neuron discharge patterns.Frontiers in neuroscience · 2023Article
- Fundamental research on surface electromyography analysis using discrete wavelet transform-an analysis of the central nervous system factors affecting muscle strength.Journal of physical therapy science · 2021Article
- A Multiday Evaluation of Real-Time Intramuscular EMG Usability with ANN.Sensors (Basel, Switzerland) · 2020Article
- Neurophysiological Characterization of a Non-Human Primate Model of Traumatic Spinal Cord Injury Utilizing Fine-Wire EMG Electrodes.Sensors (Basel, Switzerland) · 2019Article
- Single finger movements in the aging hand: changes in finger independence, muscle activation patterns and tendon displacement in older adults.Experimental brain research · 2019Article
- Non-invasive Decoding of the Motoneurons: A Guided Source Separation Method Based on Convolution Kernel Compensation With Clustered Initial Points.Frontiers in computational neuroscience · 2019Article
- Automatic Multichannel Intramuscular Electromyogram Decomposition: Progressive FastICA Peel-Off and Performance Validation.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2019Article
- A Novel Validation Approach for High-Density Surface EMG Decomposition in Motor Neuron Disease.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2018Article
- Intramuscular EMG Decomposition Basing on Motor Unit Action Potentials Detection and Superposition Resolution.Frontiers in neurology · 2018Article
- Comparative Analysis of Wavelet-based Feature Extraction for Intramuscular EMG Signal Decomposition.Journal of biomedical physics & engineering · 2017Article
- Progressive FastICA Peel-Off and Convolution Kernel Compensation Demonstrate High Agreement for High Density Surface EMG Decomposition.Neural plasticity · 2016Article
- A Novel Framework Based on FastICA for High Density Surface EMG Decomposition.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2016Article
- Examination of Poststroke Alteration in Motor Unit Firing Behavior Using High-Density Surface EMG Decomposition.IEEE transactions on bio-medical engineering · 2015Article
- Surface EMG decomposition based on K-means clustering and convolution kernel compensation.IEEE journal of biomedical and health informatics · 2015Article
- Error reduction in EMG signal decomposition.Journal of neurophysiology · 2014Article
- Techniques and applications of EMG: measuring motor units from structure to function.Journal of neurology · 2012Article
- Rigorous a posteriori assessment of accuracy in EMG decomposition.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2011Article
- High-yield decomposition of surface EMG signals.Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2010Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Decomposition of indwelling electromyographic (EMG) signals is challenging in view of the complex and often unpredictable behaviors and interactions of the action potential trains of different motor units that constitute the indwelling EMG signal. These phenomena create a myriad of problem situations that a decomposition technique needs to address to attain completeness and accuracy levels required for various scientific and clinical applications. Starting with the maximum a posteriori probability classifier adapted from the original precision decomposition system (PD I) of LeFever and De Luca (25, 26), an artificial intelligence approach has been used to develop a multiclassifier system (PD II) for addressing some of the experimentally identified problem situations. On a database of indwelling EMG signals reflecting such conditions, the fully automatic PD II system is found to achieve a decomposition accuracy of 86.0% despite the fact that its results include low-amplitude action potential trains that are not decomposable at all via systems such as PD I. Accuracy was established by comparing the decompositions of indwelling EMG signals obtained from two sensors. At the end of the automatic PD II decomposition procedure, the accuracy may be enhanced to nearly 100% via an interactive editor, a particularly significant fact for the previously indecomposable trains.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.