Motor variability during resistance training: Acceleration signal as intensity indicator

Analysis of variability in physiological time series has been shown to be an indicator of the state of the organism. Although there is evidence of the usefulness of analysis of the amount and/or structure of variability (complexity) in cycling actions, there is limited knowledge about its application in resistance exercise. The aim of this study is to find out whether variability in acceleration signals can be an indicator of intensity level in a squat task. For this purpose, an experimental design was developed in which the following participated seventy-two participants (age = 25.7 ± 4.4 years; height = 169.2 ± 9.8 cm; body mass = 67.7 ± 11.2 kg; ratio 1RM/body mass = 1.4 ± 0.3). They performed four repetitions of back squat at loads of 10%, 30%, 50%, 70%, and 90% of 1RM. Acceleration during the exercise was recorded using an inertial measurement unit (IMU) and a force platform. The variability of the movement was then analyzed using Standard Deviation (SD), Detrended Fluctuation Analysis (DFA), Fuzzy Entropy (FuzzyEn), and Sample Entropy (SampEn). For the IMU and for the force platform, significant effects were observed in all variables (p < 0.001). In pairwise comparisons, IMU showed a significant increase in motor complexity with increasing intensity, among most intensities, in DFA, FuzzyEn and SampEn. Differences in force platform were more limited, and only DFA detected differences between most intensities. The results suggest that measures of signal and acceleration variability may be a useful indicator of the relative intensity at which a squat exercise is performed.

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Journal
PLoS ONE
Published
2024-09-19
DOI
https://doi.org/10.1371/journal.pone.0307949
Citations
4
Primary Topic
Heart Rate Variability and Autonomic Control
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article
Field-Weighted Citation Impact
1.61

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article

Motor variability during resistance training: Acceleration signal as intensity indicator

Fernando García-Aguilar, Miguel López-Fernández, Rafael Sabido, Pablo Asencio et al.
4 citations
PLoS ONE
Heart Rate Variability and Autonomic Control
1.61
article

Motor variability during resistance training: Acceleration signal as intensity indicator

Fernando García-Aguilar, Miguel López-Fernández, Rafael Sabido, Pablo Asencio, Carla Caballero, Francisco Javier Moreno Hernández
article en
4 citations

Abstract

Analysis of variability in physiological time series has been shown to be an indicator of the state of the organism. Although there is evidence of the usefulness of analysis of the amount and/or structure of variability (complexity) in cycling actions, there is limited knowledge about its application in resistance exercise. The aim of this study is to find out whether variability in acceleration signals can be an indicator of intensity level in a squat task. For this purpose, an experimental design was developed in which the following participated seventy-two participants (age = 25.7 ± 4.4 years; height = 169.2 ± 9.8 cm; body mass = 67.7 ± 11.2 kg; ratio 1RM/body mass = 1.4 ± 0.3). They performed four repetitions of back squat at loads of 10%, 30%, 50%, 70%, and 90% of 1RM. Acceleration during the exercise was recorded using an inertial measurement unit (IMU) and a force platform. The variability of the movement was then analyzed using Standard Deviation (SD), Detrended Fluctuation Analysis (DFA), Fuzzy Entropy (FuzzyEn), and Sample Entropy (SampEn). For the IMU and for the force platform, significant effects were observed in all variables (p < 0.001). In pairwise comparisons, IMU showed a significant increase in motor complexity with increasing intensity, among most intensities, in DFA, FuzzyEn and SampEn. Differences in force platform were more limited, and only DFA detected differences between most intensities. The results suggest that measures of signal and acceleration variability may be a useful indicator of the relative intensity at which a squat exercise is performed.

PLoS ONEVol. 19(9)
Universitat de Miguel Hernández d'Elx (ES)
American Concrete Institute Foundation, Generalitat Valenciana, Ministerio de Ciencia e Innovación, Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital, Generalitat Valenciana
Affordable and clean energy
Openalex Percentile: Top 15%
Heart Rate Variability and Autonomic Control
1.61
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