Quantifying performance during physical activities is essential not only to optimize training and sustain progression but also to promote musculoskeletal health, prevent injuries, and support rehabilitation. Physical performance emerges from the dynamic interaction between biomechanical, physiological, and neuromuscular systems. Understanding and monitoring these interactions provides insights into functional integrity, adaptation, and early indicators of fatigue or overload.

Recent advances in medical engineering, including wearable and intra-oral sensors, multimodal fusion algorithms, and AI-driven individualized modeling, now make it possible to capture high-fidelity physiological and biomechanical data in ecologically valid conditions. These technologies bridge laboratory-based diagnostics with real-world functional monitoring, supporting applications that range from athletic performance management to clinical decision support in rehabilitation and occupational health. By combining engineering innovation with physiological interpretation, we can develop robust, scalable, and interpretable performance metrics that serve as proxies for human function, resilience, and recovery.

Despite substantial progress, the quantification of performance during physical activities remains fragmented. Devices, algorithms, and outcome metrics often lack interoperability and conceptual consistency, limiting translational use in health and clinical settings.

This Research Topic invites contributions that address these challenges by developing, validating, and integrating engineering-based methods for holistic, medically relevant performance assessment.

We welcome contributions that focus on:

I. Foundations in physiology, biomechanics, and neuromuscular control

Define clear, theory-grounded targets with operational definitions and decision thresholds relevant to health and performance. Report reliability, agreement, and sensitivity to change, and validate against established clinical or physiological references.

II. Measurement, modeling, and translational application

Advance the design and validation of innovative sensors and connected equipment (including intra-oral, wearable, or implantable devices) for in-field or clinical monitoring. Develop analysis pipelines—from task-specific algorithms to multimodal data fusion and individualized models—with explicit uncertainty quantification and interpretability linking to physiological or functional outcomes.

III. Benchmarks, open resources, and clinical translation

Provide open datasets, shared benchmarks, and standardized reporting frameworks that enable reproducibility and comparability across devices and populations. Demonstrate decision impact in real-world contexts such as injury-risk reduction, motor recovery, or long-term monitoring of physical function in sport, work, or rehabilitation.

Our Goal:
This Research Topic aims to create a shared roadmap and practical toolbox for reliable, interpretable, and clinically relevant quantification of human performance. It seeks to establish performance monitoring as a meaningful bridge between engineering innovation, physiological insight, and healthcare application—advancing both sport and medical engineering toward improved functional assessment and well-being across the lifespan.

Are you interested in contributing a manuscript to this Research Topic?

Performance Quantification During Physical Activities