Evaluation of intra-muscular EMG signal decomposition algorithms

Journal of Electromyography and Kinesiology : Official Journal of the International Society of Electrophysiological Kinesiology
D FarinaH B Olsen

Abstract

We propose and test a tool to evaluate and compare EMG signal decomposition algorithms. A model for the generation of synthetic intra-muscular EMG signals, previously described, has been used to obtain reference decomposition results. In order to evaluate the performance of decomposition algorithms it is necessary to define indexes which give a compact but complete indication about the quality of the decomposition. The indexes given by traditional detection theory are in this paper adapted to the multi-class EMG problem. Moreover, indexes related to model parameters are also introduced. It is possible in this way to compare the sensitivity of an algorithm to different signal features. An example application of the technique is presented by comparing the results obtained from a set of synthetic signals decomposed by expert operators having no information about the signal features using two different algorithms. The technique seems to be appropriate for evaluating decomposition performance and constitutes a useful tool for EMG signal researchers to identify the algorithm most appropriate for their needs.

References

Mar 1, 1990·Muscle & Nerve·P E BarkhausD B Sanders
Jul 1, 1985·IEEE Transactions on Bio-medical Engineering·K C McGillL J Dorfman
Dec 1, 1984·IEEE Transactions on Bio-medical Engineering·A GerberG S Moschytz
Jun 1, 1995·Electroencephalography and Clinical Neurophysiology·E StålbergM Aström
Mar 10, 2001·IEEE Transactions on Bio-medical Engineering·D FarinaR Merletti

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Citations

Aug 24, 2004·Medical & Biological Engineering & Computing·A Holobar, D Zazula
Aug 29, 2006·Medical & Biological Engineering & Computing·Nils OstlundJ Stefan Karlsson
Aug 29, 2006·Medical & Biological Engineering & Computing·Xiaomei RenZhiguo Yan
May 4, 2001·Journal of Electromyography and Kinesiology : Official Journal of the International Society of Electrophysiological Kinesiology·D Stashuk
Nov 15, 2008·Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences·Roberto Merletti, Dario Farina
Dec 12, 2012·Journal of Neuroengineering and Rehabilitation·Monica Rojas-MartínezJoan F Alonso
Jul 4, 2012·Journal of Electromyography and Kinesiology : Official Journal of the International Society of Electrophysiological Kinesiology·J KallioV Linnamo
May 22, 2007·Journal of Electromyography and Kinesiology : Official Journal of the International Society of Electrophysiological Kinesiology·J R FlorestalK C McGill
Mar 17, 2007·Journal of Electromyography and Kinesiology : Official Journal of the International Society of Electrophysiological Kinesiology·Bert U KleineDick F Stegeman
Apr 16, 2014·IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society·Jonathan MonsifrotDario Farina
May 31, 2014·IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society·Chenyun DaiEdward A Clancy
Jan 28, 2009·IEEE Transactions on Information Technology in Biomedicine : a Publication of the IEEE Engineering in Medicine and Biology Society·Sarbast RasheedMohamed S Kamel
Oct 4, 2012·IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society·Hossein Parsaei, Daniel W Stashuk
Jul 20, 2010·IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society·Kevin C McGill, Hamid R Marateb
Aug 12, 2010·IEEE Transactions on Bio-medical Engineering·Miki Nikolic, Christian Krarup
Mar 6, 2003·IEEE Transactions on Bio-medical Engineering·Daniel ZennaroThomas Läubli
Feb 16, 2005·IEEE Transactions on Bio-medical Engineering·Andrew Hamilton-Wright, Daniel W Stashuk
Jul 20, 2005·Journal of Neuroscience Methods·Kevin C McGillHamid R Marateb
Jul 24, 2012·Journal of Electromyography and Kinesiology : Official Journal of the International Society of Electrophysiological Kinesiology·M Rojas-MartínezR Merletti
Oct 18, 2014·Frontiers in Human Neuroscience·Jouni KallioVesa Linnamo
Nov 19, 2014·Frontiers in Human Neuroscience·Karen SøgaardGisela Sjøgaard
May 1, 2016·Journal of Neuroengineering and Rehabilitation·Mislav JordanicJoan Francesc Alonso
May 18, 2016·Computers in Biology and Medicine·Vincent CarriouFouaz Sofiane Ayachi
Apr 22, 2017·International Journal of Neural Systems·Saeed KarimimehrDario Farina

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