| 1. |
- Karlsson, Stefan, et al.
(författare)
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Enhancement of spectral analysis of myoelectric signals during static contractions using wavelet methods
- 1999
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Ingår i: IEEE Transactions on Biomedical Engineering. - : Institute of Electrical and Electronics Engineers (IEEE). - 0018-9294 .- 1558-2531. ; 46:6, s. 670-684
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we introduce wavelet packets as an alternative method for spectral analysis of surface myoelectric(ME) signals. Both computer synthesized and real ME signals are used to investigate the performance. Our simulation results show that wavelet packet estimate has slightly less mean squareerror (MSE) than Fourier method, and both methods perform similarly on the real data. Moreover, wavelet packets give us some advantages over the traditional methods such as multiresolutionof frequency, as well as its potential use for effecting time-frequency decomposition of the nonstationary signals such as the ME signals during dynamic contractions. We also introduce wavelet shrinkage method for improving spectral estimates bysignificantly reducing the MSE’s for both Fourier and wavelet packet methods.
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| 2. |
- Karlsson, Stefan, et al.
(författare)
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Estimation of surface electromyogram spectral alteration using reduced-order autoregressive model
- 2000
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Ingår i: Medical and Biological Engineering and Computing. - 0140-0118 .- 1741-0444. ; 38, s. 520-527
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Tidskriftsartikel (refereegranskat)abstract
- A new method is proposed, based on the pole phase angle (PPA) of a second-order autoregressive (AR) model, to track spectral alteration during localised muscle fatigue when analysing surface myo-electric (ME) signals. Both stationary and non-stationary, simulated and real ME signals are used to investigate different methods to track spectral changes. The real ME signals are obtained from three muscles (the right vastus lateralis, rectus femoris and vastus medialis) of six healthy male volunteers, and the simulated signals are generated by passing Gaussian white-noise sequences through digital filters with spectral properties that mimic the real ME signals. The PPA method is compared, not only with spectra-based methods, such as Fourier and AR, but also with zero crossings (ZCs) and the first AR coefficient that have been proposed in the literature as computer efficient methods. By comparing the deviation (dev), in percent, between the linear regression of the theoretical and estimated mean frequencies of the power spectra for simulated stationary (s) and non-stationary (ns) signals, in general, it is found that the PPA method (dev(s) = 4.29; dev(ns) = 1.94) gives a superior performance to ZCs (dv(s) = 8.25) and the first AR coefficient (4.18
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| 3. |
- Karlsson, Stefan, et al.
(författare)
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Time-Frequency Analysis of Myoelectric Signals During Dynamic Contractions: A Comparative Study
- 2000
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Ingår i: IEEE Transactions on Biomedical Engineering. - : Institute of Electrical and Electronics Engineers (IEEE). - 0018-9294 .- 1558-2531. ; 47:2, s. 228-238
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we introduce the nonstationary signal analysis methods to analyze the myoelectric (ME) signals during dynamic contractions by estimating the time-dependent spectral moments. The time-frequency analysis methods including the short-time Fourier transform, the Wigner–Ville distribution, the Choi–Williams distribution, and the continuous wavelet transform were compared for estimation accuracy and precision on synthesized and real ME signals. It is found that the estimates providedby the continuous wavelet transform have better accuracy and precision than those obtained with the other time-frequency analysis methods on simulated data sets. In addition, ME signals from four subjects during three different tests (maximum static voluntary contraction, ramp contraction, and repeated isokinetic contractions) were also examined.
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| 4. |
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| 5. |
- Rohlén, Robin, et al.
(författare)
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Imaging recruitment of motor units in voluntary skeletal muscle contractions using decomposition and ultrafast ultrasound imaging : A pilot study
- 2020
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Ingår i: 2020 ISEK Virtual Congress Poster Abstract Booklet. - : International Society of Electrophysiology and Kinesiology. ; , s. 141-142
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Recently our research group demonstrated a method to separate and identify the mechanical response of individual active MUs, from a large part of a muscle (4x4 cm, cross-sectional) under voluntary contractions. The method is based on ultrafast ultrasound imaging and spatiotemporal decomposition. In the present work we aimed to use this method to explore MU territory recruitment patterns at low force levels in the biceps brachii.
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| 6. |
- Rohlén, Robin, et al.
(författare)
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Segmentation of Motor Unit Territories in Ultrasound Image Sequences of Contracting Skeletal Muscle Tissue
- 2017
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Ultrasound medical imaging can be used to visualize and quantify anatomical and functional aspects of internal tissues and organs of the human body. Skeletal muscle tissue is functionally composed by motor units, which are the smallest voluntarily activatable units. In order to capture a transient phenomenon, such as the contraction mechanism, a high sample rate is required. There has been a lot of research on whole-muscle aspects in terms of skeletal muscle contraction characteristics, neuromuscular disorders, and inter-muscle segmentation. Previous studies have shown that small-scale muscle twitches can be detected using ultrasound and there are several reports on ultrasound-based detection of electro-stimulated motor unit activity. However, methods for intra-muscular ultrasound-based analysis of muscle tissue are largely underdeveloped, in particular regarding the level of motor units.Diagnostics of skeletal muscle tissue is based on analyzing features of these units by invasive, non-imaging electrophysiological methods. Here,we make progress by using non-invasive ultrasound imaging to segment motor units, which have the potential to be a non-invasive substitute and where the imaging provides an important contribution.
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| 7. |
- Rohlén, Robin, et al.
(författare)
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Ultrasound-based Imaging of Motor Units in Skeletal Muscle Tissue
- 2018
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Neuromuscular diseases hinder muscle function and may be the outcome of damage and dysfunction of the smallest voluntarily activatable units in skeletal muscle tissue, the so-called motor units (MUs). MUs generate electrical signals and analyzing these signals gives a basis to assess and diagnose MUs. The signals are captured using needle electromyography, which is an invasive and non-imaging method. Here, we showultrasound-basedimaging of MUs, via an ultrasound-based spatiotemporal decomposition framework.
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| 8. |
- Östlund, Nils, 1977-, et al.
(författare)
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Adaptive spatial filtering of multichannel surface electromyogram signals
- 2004
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Ingår i: Medical and Biological Engineering and Computing. - 0140-0118 .- 1741-0444. ; 42:6, s. 825-831
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 9. |
- Östlund, Nils, et al.
(författare)
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Adaptive spatio-temporal filtering of multichannel surface EMG signals
- 2006
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Ingår i: Medical and Biological Engineering and Computing. - : Springer Science and Business Media LLC. - 0140-0118 .- 1741-0444. ; 44:3, s. 209-215
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 10. |
- Östlund, Nils, et al.
(författare)
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Adaptive spatio-temporal filtration of bioelectrical signals
- 2005
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Ingår i: Proceedings of The 27th Annual International Conferenceof the IEEE Engineering in Medicine and Biology Society. - New York : IEEE Press. - 0780387406 ; , s. 5983-5986
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Konferensbidrag (refereegranskat)abstract
- In this paper we show how independent component analysis (ICA) algorithms can be used to perform spatio-temporal filtration of electromyographic (EMG) and electrocardiographic (ECG) signals. The technique was used to decompose the EMG signals into motor unit action potential (MUAP) trains. From the 88 outputs of the adaptive spatio-temporal filtration, three groups of different MUAP train patterns were found. The technique was also used to obtain a fetus' ECG and showed better result compared to using ICA.
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