Recurrence quantification analysis of force signals to assess neuromuscular fatigue in men and women. (July 2021)

• Record Type: Journal Article
• Authors: Chatain, Cyril; Ramdani, Sofiane; Vallier, Jean-Marc; Gruet, Mathieu
• Is Part Of: Biomedical signal processing and control. Volume 68(2021)
• Publication Date: 2021-07
• Subjects: Force signal fluctuations -- Recurrence quantification analysis -- Exercise-related fatigue -- Complexity -- Sex differences; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2021.102593
• Languages: English
• ISSNs: 1746-8094

Abstract

Highlights: RQA detects changes of force signal complexity induced by fatigue and recovery. RQA is sensitive to sex differences regarding fatigue-induced loss of complexity. We propose a methodology to apply RQA to nonstationary force signals. Abstract: Recurrence quantification analysis (RQA) is a nonlinear method providing information on the temporal structure of time series. RQA has been extensively used to explore various noisy and nonstationary physiological signals. However, the application of RQA to force signals acquired during voluntary fatiguing contractions performed until exhaustion remain to be investigated. We aimed to explore the sensitivity of the percentage of determinism (DET), an RQA predictability measure, to detect changes of force signal complexity induced by fatigue and recovery. Changes in force signal complexity were compared between women and men to explore the ability of DET measures to detect different fatigue profiles. Nineteen women and nineteen men performed intermittent isometric contractions of knee extensors at 50% of maximal voluntary contraction (MVC) until exhaustion. Participants performed MVC before, during and after the fatiguing task to assess neuromuscular fatigue. Recovery measurements were performed three minutes after exhaustion. Particular attention has been given to the selection of the input parameters of RQA and to the influence of nonstationarity. A detailed methodology is provided to apply RQA to force signals. At the whole group level, complexity decreased with fatigue then increased after recovery. Greater fatigability of men was associated with a faster loss of complexity (i.e. faster increase of DET) of force signals. After recovery, complexity returned to baseline value only for women. These findings confirm that RQA is suited to explore force signal temporal structure and is able to reveal changes of complexity induced by fatigue and recovery by taking into account sex differences.