ReviewFrontiers in sports and active living2020
Wearable Technology and Analytics as a Complementary Toolkit to Optimize Workload and to Reduce Injury Burden.
Review in Frontiers in sports and active living, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
41 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Consumer-oriented (wearable) sleep technology: a systematic SWOT analysis and recommendations for athletes and fitness enthusiasts.Frontiers in sports and active living · 2026Pooled it
- Wearable Sensor Technology to Predict Core Body Temperature: A Systematic Review.Sensors (Basel, Switzerland) · 2022Pooled it
- Artificial intelligence and wearable sensors in sports injury risk prediction: current status and future perspectives.Annals of medicine · 2026Review
- Within-Athlete Associations Between WHOOP Activity Strain, Coach-Prescribed Training Objectives, and Session-RPE in an Elite Junior Swimmer: A Longitudinal Single-Case Study.Journal of functional morphology and kinesiology · 2026Article
- Enhanced games and performance-optimized athletes: anticipating the orthopedic challenges, a narrative review.Acta orthopaedica et traumatologica turcica · 2026Review
- Emergency Clinical Decision for Sports Injury Management: A Wearable Sensor-Driven Framework from Training to Rehabilitation.Biosensors · 2026Review
- Adaptive training load optimization for track and field athletes: A reinforcement learning approach.Scientific reports · 2026Article
- Machine Learning and Non-Invasive Monitoring Technologies for Training Load Management in Women's Volleyball: A Scoping Review.Sports (Basel, Switzerland) · 2026Review
- Clinical applications of wearable sensor-based gait analysis in athletes: a systematic review for injury prevention and rehabilitation.BMC sports science, medicine & rehabilitation · 2026Article
- Artificial intelligence and wearables in sport: performance, injury risk, and wellbeing.Frontiers in artificial intelligence · 2026Review
- Attitudes toward smart sports technologies and artificial intelligence: an examination from cognitive, affective and behavioral dimensions.Frontiers in public health · 2026Article
- Multi-sensor fusion outperforms single indicators for fatigue prediction in university soccer players: a machine learning approach.Frontiers in physiology · 2026Article
- Explainable temporal deep learning for athlete-independent classification of injury-labeled days in competitive distance runners: a methodological benchmark using seven-day training-load histories.Frontiers in public health · 2026Article
- Toward autonomous artificial intelligence agents in sports science: a modular framework for development, validation, and implementation.Biology of sport · 2026Review
- Injury risk analysis of movement restriction and body asymmetry in sports injury prediction.BMC sports science, medicine & rehabilitation · 2025Article
- The Relationship Between Running Load, Strength, Muscle Architecture and Hamstring Strain Injury Across Two Seasons of Elite Male Australian Football: A Prospective Cohort Study.Sports medicine - open · 2025Article
- The Breast Impact Monitoring System: A Portable and Wearable Platform to Support Injury Prevention in Female Athletes.Sensors (Basel, Switzerland) · 2025Article
- Intelligent optimization of track and field teaching using machine learning and wearable sensors.Scientific reports · 2025Article
- Real-time monitoring of military health and readiness: a perspective on future research.Frontiers in digital health · 2025Article
- Editorial: Training load in sport: current challenges and future perspectives.Frontiers in sports and active living · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Wearable sensors enable the real-time and non-invasive monitoring of biomechanical, physiological, or biochemical parameters pertinent to the performance of athletes. Sports medicine researchers compile datasets involving a multitude of parameters that can often be time consuming to analyze in order to create value in an expeditious and accurate manner. Machine learning and artificial intelligence models may aid in the clinical decision-making process for sports scientists, team physicians, and athletic trainers in translating the data acquired from wearable sensors to accurately and efficiently make decisions regarding the health, safety, and performance of athletes. This narrative review discusses the application of commercial sensors utilized by sports teams today and the emergence of descriptive analytics to monitor the internal and external workload, hydration status, sleep, cardiovascular health, and return-to-sport status of athletes. This review is written for those who are interested in the application of wearable sensor data and data science to enhance performance and reduce injury burden in athletes of all ages.
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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.