Error reduction in EMG signal decomposition
نویسندگان
چکیده
منابع مشابه
Error reduction in EMG signal decomposition.
Decomposition of the electromyographic (EMG) signal into constituent action potentials and the identification of individual firing instances of each motor unit in the presence of ambient noise are inherently probabilistic processes, whether performed manually or with automated algorithms. Consequently, they are subject to errors. We set out to classify and reduce these errors by analyzing 1,061...
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In this chapter we refer to the decomposition of the myoelectric (ME) signal as the procedure by which the ME signal is separated into its constituents motor units action potential trains (MUAPTs). This concept is illustrated in Figure 1. The development of a system to accomplish such a decomposition will be beneficial to both researchers interested in understanding motor unit properties and be...
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Background: Electromyographic (EMG) signal decomposition is the process by which an EMG signal is decomposed into its constituent motor unit potential trains (MUPTs). A major step in EMG decomposition is feature extraction in which each detected motor unit potential (MUP) is represented by a feature vector. As with any other pattern recognition system, feature extraction has a significant impac...
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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 ...
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The quantitative analysis of decomposed electromyographic (EMG) signals reveals information for diagnosing and characterizing neuromuscular disorders. Neuromuscular jitter is an important measure that reflects the stability of the operation of a neuromuscular junction. It is conventionally measured using single fiber electromyographic (SFEMG) techniques. SFEMG techniques require substantial phy...
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ژورنال
عنوان ژورنال: Journal of Neurophysiology
سال: 2014
ISSN: 0022-3077,1522-1598
DOI: 10.1152/jn.00724.2013