Significant challenges persist, including measurement validity and reliability of sensor-derived signals and overall dataset quality
Research gap analysis derived from 3 computer_science papers in our local library.
The gap
Significant challenges persist, including measurement validity and reliability of sensor-derived signals and overall dataset quality, - Model performance and generalizability, algorithmic transparency, and equitable access are also concerns, - The gap between the potential of AI in endurance sports and the current state of research and application needs to be addressed.
Evidence profile
Sourced from the future work and inline gaps and stated research gap of the source papers, classified as general, drawn from work published between 2025 and 2026, spanning 3 journals. Those papers have been cited 21 times in total.
Research trend
Established — well-defined area with open sub-problems.
Supporting evidence — 3 representative gaps
- Artificial Intelligence in Sports Psychology and Performance Enhancement (2026) · Zenodo (CERN European Organization for Nuclear Research) · doi
The future of AI in sports psychology is promising, with several emerging technologies expected to enhance athlete performance further. One potential development is the creation of AI-powered virtual sports psychologists that provide real-time mental coaching and emotional support. These systems could help athletes manage stress and maintain focus during competitions.Another emerging trend is the integration of augmented reality and virtual reality with AI-based training programs. These technologies can simulate realistic competition environments, allowing athletes to practice mental strategies in high-pressure situations.Advancements in wearable technology will also improve real- time monitoring of psychological and physiological indicators. Future AI systems may predict performance outcomes and injury risks with even greater accuracy.
generalfuture workevidence 5/5Keywords: future sports emerging technologies performance virtual real time mental systems athletes reality psychology promising several - Expression of Concern Notice: Real Time Monitoring Research on Rehabilitation Effect of Artificial Intelligence Wearable Equipment on Track and Field Athletes (2026) · EAI Endorsed Transactions on Pervasive Health and Technology · doi
Distribution of sports medicine problems 8 EAI Endorsed Transactions on Pervasive Health and Technology | Volume 10 | 2024 | Real Time Monitoring Research on Rehabilitation Effect of Artificial Intelligence Wearable Equipment on Track and Field Athletes The limitations of this study are that the study population was relatively small, and the exercise conditions could be particular, e.
generalinline gapsevidence 5/5Keywords: distribution sports medicine problems endorsed transactions pervasive health technology volume real time monitoring rehabilitation effect - Artificial Intelligence in Endurance Sports: Metabolic, Recovery, and Nutritional Perspectives (2025) · Nutrients · cited 21× · doi
Significant challenges persist, including measurement validity and reliability of sensor-derived signals and overall dataset quality, - Model performance and generalizability, algorithmic transparency, and equitable access are also concerns, - The gap between the potential of AI in endurance sports and the current state of research and application needs to be addressed.
generalstated research gapevidence 5/5Keywords: significant challenges persist including measurement validity reliability sensor-derived
Questions about this gap
Explore this gap further
Run this gap as a query across open scholarly engines for the latest related literature.
Working on this gap? Review it with us.
AI Review reads your manuscript in one pass with 8 specialist agents, calibrated on 69K+ real peer reviews.
Tools for your next paper
Related gaps in Computer Science
- Previous studies have predominantly focused on analyzingPrevious studies have predominantly focused on analyzing the relationship between the built environment and urban vitality at either a…
- Existing object detection models struggle to effectivelyExisting object detection models struggle to effectively capture cross-scale contextual information and multi-level semantic…
- The complexity of the throwing motion, which involvesThe complexity of the throwing motion, which involves high abduction angles and explosive movements. Another challenge is the need to…
- The lack of conversion of surveillance microdataThe lack of conversion of surveillance microdata into actionable epidemiological intelligence. The need for a reproducible dataset and…