ArticleFrontiers in public health2024
Analyzing activity and injury risk in elite curling athletes: seven workload monitoring metrics from session-RPE.
Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Acute:chronic workload ratio and load management for team sports: a multilevel meta-analysis.Frontiers in public health · 2026Pooled it
- Analyzing Workload-Monitoring Consistency and Same-Week Injury-Classification Performance in Female Adolescent Swimmers: An Exploratory Session-RPE and Neural Network Study.Life (Basel, Switzerland) · 2026Article
- The Relationship between Training Load Indicators and the Total Quality Recovery Scale during the Preseason Period in Collegiate Taekwondo Athletes.Journal of human kinetics · 2026Article
- Research progress in exercise-induced fatigue monitoring and injury early warning based on flexible sensing textiles and deep learning.Frontiers in bioengineering and biotechnology · 2026Review
- Effects of sliding techniques on lower limb biomechanics and muscle synergy during curling delivery: a focus on joint kinetics and muscle coordination.Frontiers in human neuroscience · 2025Article
- Session-RPE for quantifying workload in olympic curling athletes.Frontiers in sports and active living · 2025Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: The study aimed to compare the differences in the performance of seven session-rating of perceived exertion (RPE)-derived metrics (coupled and uncoupled acute: chronic workload ratio (ACWR), weekly ratio of workload change, monotony, standard deviation of weekly workload change, exponentially weighted moving average (EWMA), and robust exponential decreasing index (REDI)) in classifying the performance of an injury prediction model after taking into account the time series (no latency, 5-day latency, and 10-day latency). Design: The study documented the RPE of eight curlers in their daily training routine for 211 days prior to the Olympic Games. Methods: Seven Session-RPE (sRPE)-derived metrics were used to build models at three time series nodes using logistic regression and multilayer perceptron. Receiver operating characteristic plots were plotted to evaluate the model's performance. Results: Among the seven sRPE-derived metrics multilayer perceptron models, the model without time delay (same-day load corresponding to same-day injury) exhibited the highest average classification performance (86.5%, AUC = 0.773). EMWA and REDI demonstrated the best classification performance (84.4%, Conclusion: EWMA without delay is a more sensitive indicator for detecting injury risk.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.