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A software package for the decomposition of long-term multichannel EMG signals using wavelet coefficients.
Journal article

A software package for the decomposition of long-term multichannel EMG signals using wavelet coefficients.

  • Zennaro D Institute of Hygiene and Applied Physiology and the Signal and Information Processing Laboratory, Swiss Federal Institute of Technology Zurich, Zurich 8092, Switzerland. daniel.zennaro@alumni.ethz.ch
  • Wellig P
  • Koch VM
  • Moschytz GS
  • Läubli T
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  • 2003-03-06
Published in:
  • IEEE transactions on bio-medical engineering. - 2003
Action Potentials
Adult
Algorithms
Cluster Analysis
Computer Simulation
Diagnosis, Computer-Assisted
Electromyography
False Negative Reactions
False Positive Reactions
Female
Fingers
Humans
Internet
Male
Middle Aged
Models, Neurological
Monitoring, Ambulatory
Motor Neurons
Movement
Muscle, Skeletal
Musculoskeletal Diseases
Pattern Recognition, Automated
Porphyrins
Reproducibility of Results
Shoulder
Signal Processing, Computer-Assisted
Software
English This paper presents a method to decompose multichannel long-term intramuscular electromyogram (EMG) signals. In contrast to existing decomposition methods which only support short registration periods or single-channel recordings of signals of constant muscle effort, the decomposition software EMG-LODEC (ElectroMyoGram LOng-term DEComposition) is especially designed for multichannel long-term recordings of signals of slight muscle movements. A wavelet-based, hierarchical cluster analysis algorithm estimates the number of classes [motor units (MUs)], distinguishes single MUAPs from superpositions, and sets up the shape of the template for each class. Using three channels and a weighted averaging method to track action potential (AP) shape changes improve the analysis. In the last step, nonclassified segments, i.e., segments containing superimposed APs, are decomposed into their units using class-mean signals. Based on experiments on simulated and long-term recorded EMG signals, our software is capable of providing reliable decompositions with satisfying accuracy. EMG-LODEC is suitable for the study of MU discharge patterns and recruitment order in healthy subjects and patients during long-term measurements.
Language
  • English
Open access status
closed
Identifiers
Persistent URL
https://sonar.ch/global/documents/154091
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