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Adaptive signal processing of surface electromyogram signals
Umeå University, Faculty of Medicine, Radiation Sciences.
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.
Series
Umeå University medical dissertations, ISSN 0346-6612 ; 1009
Keyword [en]
Signalbehandling, electromyography, signal processing
Keyword [sv]
Signalbehandling
Research subject
Biomedical Radiation Science
Identifiers
URN: urn:nbn:se:umu:diva-743ISBN: 91-7264-033-2 (print)OAI: oai:DiVA.org:umu-743DiVA: diva2:144395
Public defence
2006-04-28, 244, 7, Norrlands universitetssjukhus, Umeå, 13:00 (English)
Opponent
Supervisors
Available from: 2006-04-05 Created: 2006-04-05 Last updated: 2010-01-18Bibliographically approved
List of papers
1. Location of innervation zone determined with multichannel surface electromyography using an optical flow technique.
Open this publication in new window or tab >>Location of innervation zone determined with multichannel surface electromyography using an optical flow technique.
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.

Keyword
Electromyography; Surface EMG; Multichannel; Optical flow; Innervation zone
Identifiers
urn:nbn:se:umu:diva-5039 (URN)10.1016/j.jelekin.2006.06.002 (DOI)16890457 (PubMedID)
Available from: 2006-04-05 Created: 2006-04-05Bibliographically approved
2. Improved maximum frequency estimation with application to instantaneous mean frequency estimation of surface electromyography
Open this publication in new window or tab >>Improved maximum frequency estimation with application to instantaneous mean frequency estimation of surface electromyography
2004 (English)In: IEEE Transactions on Biomedical Engineering, ISSN 0018-9294, E-ISSN 1558-2531, Vol. 51, no 9, 1541-1546 p.Article in journal (Refereed) Published
Abstract [en]

The purpose of this study was to improve the maximum-frequency estimation. Three methods to estimate the maximum frequency of a bandlimited signal with additive white noise were compared. Two existing methods, the threshold-crossing method (TCM) and the hybrid method, were modified for time-frequency representations. A novel approach, the running-block threshold method (RBTM), was introduced. Based on calculation of detection probability (sensitivity) the RBTM improved the maximum-frequency estimate as compared with the TCM. The maximum-frequency estimation methods were also used to determine the integration interval for instantaneous mean-frequency (IMNF) estimation from synthesized surface electromyography containing white noise. Results showed that the IMNF estimate was improved by using any of the three methods and that the RBTM gave the best IMNF estimate.

Keyword
Electromyography (EMG), instantaneous mean frequency, maximum frequency, varying signal-to-noise ratio
National Category
Medical Engineering
Research subject
Signal Processing
Identifiers
urn:nbn:se:umu:diva-5040 (URN)10.1109/TBME.2004.827930 (DOI)15376502 (PubMedID)
Available from: 2006-04-05 Created: 2006-04-05 Last updated: 2013-01-03
3. Adaptive spatial filtering of multichannel surface electromyogram signals
Open this publication in new window or tab >>Adaptive spatial filtering of multichannel surface electromyogram signals
2004 (English)In: Medical and Biological Engineering and Computing, ISSN 0140-0118, E-ISSN 1741-0444, Vol. 42, no 6, 825-831 p.Article in journal (Refereed) Published
Abstract [en]

Spatial filtering of surface electromyography (EMG) signals can be used to enhance single motor unit action potentials (MUAPs). Traditional spatial filters for surface EMG do not take into consideration that some electrodes could have poor skin contact. In contrast to the traditional a priori defined filters, this study introduces an adaptive spatial filtering method that adapts to the signal characteristics. The adaptive filter, the maximum kurtosis filter (MKF), was obtained by using the linear combination of surrounding channels that maximises kurtosis. The MKF and conventional filters were applied to simulated EMG signals and to real EMG signals recorded with an electrode grid to evaluate their performance in detecting single motor units. The MKF was compared with conventional spatial filtering methods. Simulated signals, with different levels of spatially correlated noise, were used for comparison. The influence of one electrode with poor skin contact was also investigated. The MKF was found to be considerably better at enhancing a single MUAP than conventional methods for all levels of spatial correlation of the noise. For a spatial correlation of 0.97 of the noise, the improvement in the signal-to-noise ratio, where a MUAP could be detected, was at least 6dB. With a simulated poor skin contact for one electrode, the improvement over the other methods was at least 19 dB.

Keyword
Electromyography, EMG, multichannel, spatial filter, kurtosis
National Category
Medical Engineering
Research subject
Signal Processing
Identifiers
urn:nbn:se:umu:diva-14746 (URN)15587475 (PubMedID)
Available from: 2006-11-10 Created: 2006-11-10 Last updated: 2017-06-01
4. Adaptive spatio-temporal filtering of multichannel surface EMG signals
Open this publication in new window or tab >>Adaptive spatio-temporal filtering of multichannel surface EMG signals
2006 (English)In: Medical and Biological Engineering and Computing, ISSN 0140-0118, E-ISSN 1741-0444, Vol. 44, no 3, 209-215 p.Article in journal (Refereed) Published
Abstract [en]

A motor unit (MU) is defined as an anterior horn cell, its axon, and the muscle fibres innervated by the motor neuron. A surface electromyogram (EMG) is a superposition of many different MU action potentials (MUAPs) generated by active MUs. The objectives of this study were to introduce a new adaptive spatio-temporal filter, here called maximum kurtosis filter (MKF), and to compare it with existing filters, on its performance to detect a single MUAP train from multichannel surface EMG signals. The MKF adaptively chooses the filter coefficients by maximising the kurtosis of the output. The proposed method was compared with five commonly used spatial filters, the weighted low-pass differential filter (WLPD) and the marginal distribution of a continuous wavelet transform. The performance was evaluated using simulated EMG signals. In addition, results from a multichannel surface EMG measurement fro from a subject who had been previously exposed to radiation due to cancer were used to demonstrate an application of the method. With five time lags of the MKF, the sensitivity was 98.7% and the highest sensitivity of the traditional filters was 86.8%, which was obtained with the WLPD. The positive predictivities of these filters were 87.4 and 80.4%, respectively. Results from simulations showed that the proposed spatio-temporal filtration technique significantly improved performance as compared with existing filters, and the sensitivity and the positive predictivity increased with an increase in number of time lags in the filter.

Keyword
Electromyography, EMG, Multichannel, Spatio-temporal filter, Kurtosis
National Category
Medical Engineering
Research subject
Signal Processing
Identifiers
urn:nbn:se:umu:diva-13355 (URN)10.1007/s11517-006-0029-1 (DOI)000240031900006 ()16937162 (PubMedID)
Available from: 2006-11-06 Created: 2006-11-06 Last updated: 2013-10-02Bibliographically approved
5. Firing rate and conduction velocity of single motor units in the trapezius muscle in fibromyalgia patients and healthy controls.
Open this publication in new window or tab >>Firing rate and conduction velocity of single motor units in the trapezius muscle in fibromyalgia patients and healthy controls.
Show others...
2008 (English)In: Journal of Electromyography & Kinesiology, ISSN 1050-6411, E-ISSN 1873-5711, Vol. 18, no 5, 707-716 p.Article in journal (Refereed) Published
Abstract [en]

Fibromyalgia is a common chronic pain condition in the population (2-4%), which often is associated with prominent negative consequences with respect to participation in daily activities. There are several reports in the literature concerning the effects of acute experimental pain on motor control. However, a more heterogeneous picture exists in the literature with respect to whether chronic pain conditions affect motor control. This study compares firing rate and conduction velocity (CV) of single motor units (MUs) in the trapezius muscle of fibromyalgia patients (FM) and healthy controls (CON). Multi-channel surface electromyography was used to estimate both MU firing rate and CV because this technique allows simultaneous estimation of both these variables and the measurements are easy and non-invasive. In this study, 29 FM and 30 CON subjects participated and performed isometric shoulder elevations using weights up to 4 kg. No significant differences in the firing rate of MUs in the trapezius muscle were found between the FM and CON groups (95% confidence interval was -1.9 and 1.3 pulses per second). There were no significant differences in CV between the groups at 1 and 2 kg load. However, the FM group had significantly higher CV in contractions without external load (p=0.004). We were unable to confirm the pain-adaptation model since no differences in firing rate between the two groups were found. CV was significantly higher in FM than in healthy controls; this might be due to alterations in histopathology and microcirculation.

Keyword
Electromyography, EMG, fibromyalgia, firing rate, conduction velocity
Identifiers
urn:nbn:se:umu:diva-10458 (URN)doi:10.1016/j.jelekin.2007.02.016 (DOI)17459728 (PubMedID)
Available from: 2008-09-12 Created: 2008-09-12 Last updated: 2011-08-23Bibliographically approved

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