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Training-Intensity Distribution in Road Cyclists: Objective Versus Subjective Measures.
Summary
Using rating of perceived exertion (RPE) to measure training intensity in cyclists yields different results than heart rate (HR) or power output (PO). This impacts how training load is assessed and prescribed.
Area of Science:
- Sports Science
- Exercise Physiology
- Cycling Performance
Background:
- Accurate training-intensity distribution is crucial for optimizing performance in well-trained cyclists.
- Different physiological and subjective measures exist to quantify exercise intensity, including rating of perceived exertion (RPE), heart rate (HR), and power output (PO).
- The congruence of these measures in defining training zones remains an area of investigation.
Purpose of the Study:
- To compare training-intensity distribution in well-trained cyclists using rating of perceived exertion (RPE), heart rate (HR), and power output (PO).
- To identify discrepancies in training zone allocation based on different intensity quantification methods.
- To understand the implications of these discrepancies for training prescription and load monitoring.
Main Methods:
- Fifteen road cyclists underwent a 10-week training period.
- Training data were collected and intensity distribution was analyzed using RPE, HR, and PO.
- A 3-zone model was applied, with HR and PO zones based on lactate thresholds, and RPE zones defined on a 10-point scale.
Main Results:
- Significant differences were observed in time spent across training zones when using RPE versus HR and PO.
- RPE resulted in substantially less time in Zone 1 and more time in Zones 2 and 3 compared to HR and PO.
- These differences were statistically significant (P < .001) across all zones.
Conclusions:
- Training-intensity distribution analysis in cyclists is highly dependent on the chosen intensity measure (RPE, HR, or PO).
- Quantification using RPE leads to a different distribution of training load compared to HR and PO.
- The selection of an intensity measure has critical implications for training load quantification, prescription, and overall training evaluation.
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