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Related Experiment Video

Updated: Jun 17, 2025

Force and Position Control in Humans - The Role of Augmented Feedback
06:31

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Published on: June 19, 2016

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Examining the alignment between subjective effort and objective force production.

Katja Rewitz1,2, Sebastian Schindler3, Wanja Wolff1,2

  • 1Dynamics of Human Performance Regulation Laboratory, Institue of Human Movement Science, University of Hamburg, Hamburg, Germany.

Plos One
|August 9, 2024
PubMed
Summary
This summary is machine-generated.

The relationship between perceived exertion (RPE) and actual performance is complex. Factors like effort level, time, and mental load influence how accurately RPE reflects physical output.

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Area of Science:

  • Exercise Physiology
  • Human Performance
  • Psychophysics

Background:

  • Ratings of Perceived Exertion (RPE) are widely used for exercise intensity prescription.
  • A core assumption is that RPE consistently reflects objective performance.
  • However, the precise nature of this RPE-performance alignment is not fully understood.

Purpose of the Study:

  • To investigate the degree and shape of alignment between RPE and objective force production.
  • To examine how time and mental effort influence this RPE-performance relationship.
  • To understand the nuances of RPE-based exercise prescription.

Main Methods:

  • A randomized within-subjects experiment with 43 participants.
  • Utilized a grip-to-scale method with a handgrip dynamometer.
  • Participants produced four target RPE levels (20%, 40%, 60%, 80% of maximum strength).

Main Results:

  • RPE-force alignment varied across RPE levels, with a larger discrepancy in the 60-80% interval.
  • Force output decreased over time at constant RPE, more so at lower levels.
  • Anticipating mental effort slightly altered RPE-performance alignment.

Conclusions:

  • The mapping of perceived exertion onto objective performance is intricate and non-linear.
  • Time and mental effort are significant moderators of the RPE-performance relationship.
  • Understanding these dynamics is crucial for accurate RPE-based training load prescription.