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Motor variability during resistance training: Acceleration signal as intensity indicator.

Miguel López-Fernández1, Fernando García-Aguilar1, Pablo Asencio1

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Summary

Movement variability analysis, using acceleration signals, can indicate exercise intensity during squats. This research explores complexity measures like DFA, FuzzyEn, and SampEn to assess workout load.

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Area of Science:

  • Biomechanics
  • Exercise Physiology
  • Signal Analysis

Background:

  • Physiological time series variability analysis indicates organism state.
  • Complexity analysis is useful in cycling but understudied in resistance exercise.

Purpose of the Study:

  • To determine if acceleration signal variability indicates intensity in squat exercises.
  • Investigate the application of complexity measures in resistance training.

Main Methods:

  • Seventy-two participants performed squats at 10-90% of 1RM.
  • Acceleration data collected via IMU and force platform.
  • Variability analyzed using Standard Deviation (SD), DFA, FuzzyEn, and SampEn.

Main Results:

  • Significant effects of intensity on variability measures for both IMU and force platform (p < 0.001).
  • IMU data showed increased motor complexity with higher intensity for DFA, FuzzyEn, and SampEn.
  • Force platform data showed fewer differences, with DFA detecting most intensity variations.

Conclusions:

  • Acceleration signal variability, particularly motor complexity, is a potential indicator of relative intensity in squat exercises.
  • IMU-based complexity measures offer a promising approach for monitoring resistance training intensity.