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Location of innervation zone determined with multichannel surface electromyography using an optical flow technique.
Umeå University, Faculty of Medicine, Radiation Sciences.
2007 (English)In: Journal of Electromyography & Kinesiology, ISSN 1050-6411, Vol. 17, no 5, 549-555 p.Article in journal (Refereed) Published
Abstract [en]

Multichannel surface electromyography has developed towards more channels and higher spatial resolution. This allows the study of multichannel electromyograms as images of the potential distribution on the skin. In this paper, a method that estimates the motion of the potential distribution using an optical-flow-based technique is introduced. The optical flow is a vector field that describes how images change with time. The aim of this study was to introduce a new method for innervation zone (IZ) localization and to evaluate its performance. The new method was compared with a method that uses the position of the lowest root-mean-square (RMS) value in an electrode array as an estimate of the IZ localization. Comparisons were made with both simulated signals and with recorded multichannel electromyogram signals. Simulations showed that the methods performed similarly for high signal-to-noise ratio (SNR) and that the optical-flow-based method was superior for lower SNR. When the experimental signals were used, localization with the optical-flow-based method gave a mean absolute deviation of 2.4mm from the location given by an expert group. The lowest RMS method gave a significantly higher deviation (13.6mm). Due to the low computational complexity of the optical flow algorithm it is possible to get the estimations of the IZ localization in real time.

Place, publisher, year, edition, pages
2007. Vol. 17, no 5, 549-555 p.
Keyword [en]
Electromyography; Surface EMG; Multichannel; Optical flow; Innervation zone
URN: urn:nbn:se:umu:diva-5039DOI: 10.1016/j.jelekin.2006.06.002PubMedID: 16890457OAI: diva2:144390
Available from: 2006-04-05 Created: 2006-04-05Bibliographically approved
In thesis
1. Adaptive signal processing of surface electromyogram signals
Open this publication in new window or tab >>Adaptive signal processing of surface electromyogram signals
2006 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Electromyography is the study of muscle function through the electrical signals from the muscles. In surface electromyography the electrical signal is detected on the skin. The signal arises from ion exchanges across the muscle fibres’ membranes. The ion exchange in a motor unit, which is the smallest unit of excitation, produces a waveform that is called an action potential (AP). When a sustained contraction is performed the motor units involved in the contraction will repeatedly produce APs, which result in AP trains. A surface electromyogram (EMG) signal consists of the superposition of many AP trains generated by a large number of active motor units. The aim of this dissertation was to introduce and evaluate new methods for analysis of surface EMG signals.

An important aspect is to consider where to place the electrodes during the recording so that the electrodes are not located over the zone where the neuromuscular junctions are located. A method that could estimate the location of this zone was presented in one study.

The mean frequency of the EMG signal is often used to estimate muscle fatigue. For signals with low signal-to-noise ratio it is important to limit the integration intervals in the mean frequency calculations. Therefore, a method that improved the maximum frequency estimation was introduced and evaluated in comparison with existing methods.

The main methodological work in this dissertation was concentrated on finding single motor unit AP trains from EMG signals recorded with several channels. In two studies single motor unit AP trains were enhanced by using filters that maximised the kurtosis of the output. The first of these studies used a spatial filter, and in the second study the technique was expanded to include filtration in time. The introduction of time filtration resulted in improved performance, and when the method was evaluated in comparison with other methods that use spatial and/or temporal filtration, it gave the best performance among them. In the last study of this dissertation this technique was used to compare AP firing rates and conduction velocities in fibromyalgia patients as compared with a control group of healthy subjects.

In conclusion, this dissertation has resulted in new methods that improve the analysis of EMG signals, and as a consequence the methods can simplify physiological research projects.

Place, publisher, year, edition, pages
Umeå: Strålningsvetenskaper, 2006. 52 p.
Umeå University medical dissertations, ISSN 0346-6612 ; 1009
Signalbehandling, electromyography, signal processing, Signalbehandling
Research subject
Biomedical Radiation Science
urn:nbn:se:umu:diva-743 (URN)91-7264-033-2 (ISBN)
Public defence
2006-04-28, 244, 7, Norrlands universitetssjukhus, Umeå, 13:00 (English)
Available from: 2006-04-05 Created: 2006-04-05 Last updated: 2010-01-18Bibliographically approved

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