Journal ArticleDOI
Surface EMG based muscle fatigue evaluation in biomechanics
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TLDR
Time domain, frequency domain, time-frequency and time-scale representations, and other methods such as fractal analysis and recurrence quantification analysis are described succinctly and are illustrated with their biomechanical applications, research or clinical alike.About:
This article is published in Clinical Biomechanics.The article was published on 2009-05-01. It has received 694 citations till now.read more
Citations
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Journal ArticleDOI
An official American Thoracic Society/European Respiratory Society statement: update on limb muscle dysfunction in chronic obstructive pulmonary disease
François Maltais,Marc Decramer,Richard Casaburi,Esther Barreiro,Yan Burelle,Richard Debigaré,P. N. Richard Dekhuijzen,Frits M.E. Franssen,Ghislaine Gayan-Ramirez,Joaquim Gea,Harry R. Gosker,Rik Gosselink,Maurice Hayot,Sabah N. A. Hussain,Wim Janssens,Micheal I. Polkey,Josep Roca,Didier Saey,Annemie M. W. J. Schols,Martijn A. Spruit,Michael C Steiner,Tanja Taivassalo,Thierry Troosters,Ioannis Vogiatzis,Peter D. Wagner +24 more
TL;DR: The purpose of this document is to update the 1999 ATS/ERS statement on limb muscle dysfunction in COPD with important advances in the understanding of the extent and nature of the structural alterations in limb muscles in patients with COPD.
Journal ArticleDOI
Current state of digital signal processing in myoelectric interfaces and related applications
TL;DR: The major benefits and challenges of myoelectric interfaces are evaluated and recommendations are given, for example, for electrode placement, sampling rate, segmentation, and classifiers.
Journal ArticleDOI
Electromyographic models to assess muscle fatigue.
TL;DR: This paper provides an overview of linear and non-linear sEMG models for estimating muscle fatigue, their ability to assess power loss and their limitations due to neuromuscular changes after a training period.
Book ChapterDOI
The Usefulness of Mean and Median Frequencies in Electromyography Analysis
TL;DR: Rich useful information can be obtained from the muscles and researchers can use such information in a wide class of clinical and engineering applications by measuring surface electromyography (EMG) signals, which can be computed in numerical form from a finite length time interval.
Journal ArticleDOI
Extraction and analysis of multiple time window features associated with muscle fatigue conditions using sEMG signals
TL;DR: The k-nearest neighbour algorithm is found to be the most accurate in classifying the features, with a maximum accuracy of 93% with the features selected using information gain ranking.
References
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A new look at the statistical model identification
TL;DR: In this article, a new estimate minimum information theoretical criterion estimate (MAICE) is introduced for the purpose of statistical identification, which is free from the ambiguities inherent in the application of conventional hypothesis testing procedure.
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The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis
Norden E. Huang,Zheng Shen,Steven R. Long,Man-Li C. Wu,Hsing H. Shih,Quanan Zheng,Nai-Chyuan Yen,C. C. Tung,Henry H. Liu +8 more
TL;DR: In this paper, a new method for analysing nonlinear and nonstationary data has been developed, which is the key part of the method is the empirical mode decomposition method with which any complicated data set can be decoded.
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An algorithm for the machine calculation of complex Fourier series
J.W. Cooley,John W. Tukey +1 more
TL;DR: Good generalized these methods and gave elegant algorithms for which one class of applications is the calculation of Fourier series, applicable to certain problems in which one must multiply an N-vector by an N X N matrix which can be factored into m sparse matrices.
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Discrete-Time Signal Processing
TL;DR: In this paper, the authors provide a thorough treatment of the fundamental theorems and properties of discrete-time linear systems, filtering, sampling, and discrete time Fourier analysis.
Journal ArticleDOI
The use of fast Fourier transform for the estimation of power spectra: A method based on time averaging over short, modified periodograms
TL;DR: In this article, the use of the fast Fourier transform in power spectrum analysis is described, and the method involves sectioning the record and averaging modified periodograms of the sections.