Journal ArticleDOI
Surface electromyography based muscle fatigue progression analysis using modified B distribution time–frequency features
P. A. Karthick,S. Ramakrishnan +1 more
TLDR
MBD based time–frequency spectrum is able to provide the instantaneous variations of frequency components associated with fatiguing contractions and it is found that the values of IMDF, IMNF and InstSPR in LFB region have lowest variability across different subjects in comparison with other two features.About:
This article is published in Biomedical Signal Processing and Control.The article was published on 2016-04-01. It has received 45 citations till now. The article focuses on the topics: Time–frequency analysis & Frequency band.read more
Citations
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Journal ArticleDOI
Surface electromyography based muscle fatigue detection using high-resolution time-frequency methods and machine learning algorithms.
TL;DR: The proposed methods are found to be capable of handling the nonstationary and multicomponent variations of sEMG signals recorded in dynamic fatiguing contractions and the combination of EMBD- polynomial kernel based SVM could be used to detect the dynamic muscle fatigue conditions.
Resolution Measure Criteria for the Objective Assessment of the Performance of Quadratic Time-Frequency Distributions
Boualem Boashash,Victor Sucic +1 more
TL;DR: In this paper, a measure for assessing the resolution performance of time-frequency distributions (TFDs) in separating closely spaced components in the timefrequency domain is defined, taking into account key attributes of TFDs, such as components mainlobes and sidelobes, and cross terms.
Journal ArticleDOI
A New Competitive Binary Grey Wolf Optimizer to Solve the Feature Selection Problem in EMG Signals Classification
TL;DR: The experimental results show the superiority of CBGWO not only in classification performance, but also feature reduction, as it has a very low computational cost, which is more suitable for real world application.
Journal ArticleDOI
Deep Learning on 1-D Biosignals: a Taxonomy-based Survey
TL;DR: A large variability of research with respect to data, application, and network topology is demonstrated and future research is expected to focus on the standardization of deep learning architectures and on the optimization of the network parameters to increase performance and robustness.
Journal ArticleDOI
EMG Processing Based Measures of Fatigue Assessment during Manual Lifting.
E. F. Shair,Siti Anom Ahmad,Mohammad Hamiruce Marhaban,S.B. Mohd Tamrin,Abdul Rahim Abdullah +4 more
TL;DR: In this paper, the impact of EMG processing based measures in fatigue assessment during manual lifting are reviewed in this paper, which will greatly benefit researchers who need a bird's eye view of the biosignal processing which are currently available, thus determining the best possible techniques for lifting applications.
References
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Journal ArticleDOI
Improved time-frequency representation of multicomponent signals using exponential kernels
H.-I. Choi,William J. Williams +1 more
TL;DR: In this article, a time-frequency distribution of L. Cohen's (1966) class is introduced, which is called exponential distribution (ED) after its exponential kernel function, and the authors interpret the ED from the spectral density-estimation point of view.
Journal ArticleDOI
Feature reduction and selection for EMG signal classification
TL;DR: In this study, most complete and up-to-date thirty-seven time domain and frequency domain features have been proposed and it is indicated that most time domain features are superfluity and redundancy.
Book
Time-Frequency Signal Analysis and Processing: A Comprehensive Reference
TL;DR: Time Frequency Signal Analysis and Processing focuses on advanced techniques and methods that allow a refined extraction and processing of information, allowing efficient and effective decision making that would not be possible with classical techniques.
Journal ArticleDOI
Characterization of Surface EMG Signal Based on Fuzzy Entropy
TL;DR: Its performance on characterizing surface EMG signals, as well as independent, identically distributed (i.i.d.) random numbers and periodical sinusoidal signals, shows that FuzzyEn can more efficiently measure the regularity of time series.
Journal ArticleDOI
Surface EMG based muscle fatigue evaluation in biomechanics
TL;DR: 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.