Title :
Fuzzy central tendency measure for time series variability analysis with application to fatigue electromyography signals
Author :
Hong-Bo Xie ; Dokos, Socrates
Author_Institution :
Grad. Sch. of Biomed. Eng., Univ. of New South Wales, Sydney, NSW, Australia
Abstract :
A new method, namely fuzzy central tendency measure (fCTM) analysis, that could enable measurement of the variability of a time series, is presented in this study. Tests on simulated data sets show that fCTM is superior to the conventional central tendency measure (CTM) in several respects, including improved relative consistency and robustness to noise. The proposed fCTM method was applied to electromyograph (EMG) signals recorded during sustained isometric contraction for tracking local muscle fatigue. The results showed that the fCTM increased significantly during the development of muscle fatigue, and it was more sensitive to the fatigue phenomenon than mean frequency (MNF), the most commonly-used muscle fatigue indicator.
Keywords :
electromyography; fatigue; fuzzy set theory; time series; MNF; conventional central tendency measure; fCTM method; fatigue electromyography signals; fatigue phenomenon; fuzzy central tendency measure analysis; local muscle fatigue tracking; mean frequency; muscle fatigue development; muscle fatigue indicator; sustained isometric contraction; time series variability analysis; Electromyography; Fatigue; Logistics; Muscles; Noise; Time series analysis;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE
Conference_Location :
Osaka
DOI :
10.1109/EMBC.2013.6609438