EMG signal decomposition: how can it be accomplished and used?
- 25 April 2001
- journal article
- Published by Elsevier in Journal of Electromyography and Kinesiology
- Vol. 11 (3) , 151-173
- https://doi.org/10.1016/s1050-6411(00)00050-x
Abstract
No abstract availableKeywords
This publication has 64 references indexed in Scilit:
- Recruitment of low threshold motor-units in the trapezius muscle in different static arm positionsErgonomics, 1999
- Quantitative Motor Unit Potential AnalysisJournal Of Clinical Neurophysiology, 1996
- Characteristics of motor unit discharge in subjects with hemiparesisMuscle & Nerve, 1995
- NNERVE: Neural Network Extraction of Repetitive Vectors for Electromyography. I. AlgorithmIEEE Transactions on Biomedical Engineering, 1994
- NNERVE: Neural Network Extraction of Repetitive Vectors for Electromyography. II. Performance analysisIEEE Transactions on Biomedical Engineering, 1994
- Simulation of electromyographic signalsJournal of Electromyography and Kinesiology, 1993
- Probabilistic inference-based classification applied to myoelectric signal decompositionIEEE Transactions on Biomedical Engineering, 1992
- Age effects on properties of motor unit action potentials: ADEMG analysisAnnals of Neurology, 1988
- Separation of superimposed signals by a cross-correlation methodIEEE Transactions on Acoustics, Speech, and Signal Processing, 1983
- A statistical analysis of interdependence in character sequencesInformation Sciences, 1975