Dear Colleagues,

The definition of “biomechanics” originates from Ancient Greek combining “βίος” meaning “life” and “μηχανική” meaning “mechanics”, reflecting the application of mechanical principles to understand movement. Human movement is complex and relies on the integration of the central and peripheral nervous systems, sensory inputs, as well as musculoskeletal function (energy production/delivery) and co-ordination (of muscles, tendons, joints). Instrumented biomechanical evaluation provides objective outcomes that may be quantified and interpreted following an understanding of movement principles and underlying mechanisms.

Characterising “movement in context” represents the cornerstone of current biomechanical analyses of human movement, fundamental to understanding and optimising physical function and performance in a variety of settings (i.e. clinic, real-world, performance/sporting applications). Multi-disciplinary approaches to the evaluation of human movement are vital; movement specialists must select the most appropriate measurement tool whilst extracting features that are important, meaningful, fit for purpose, and robust. Biomechanists are key in this new age generation of multi-disciplinary expertise. Only by encouraging hybrid, collaborative thinking will we fuse the knowledge necessary to deliver personalised interventions that are feasible, effective and sustainable in the current healthcare ecosystem and sporting profession.

This Special Issue is devoted to celebrating recent advances in biomechanics, specifically innovative approaches for the observation, analysis and evaluation of human movement. We cordially invite contributions that encompass a broad range of biomechanical applications including advanced and innovative techniques for assessing clinical movement; characterising mobility deficits; optimising musculoskeletal function through intervention and rehabilitation; injury prevention; athletic performance; and sporting applications. Novel approaches to the acquisition of biomechanical data (i.e., markerless motion capture, multi-modal/multi-sensor techniques, approaches to handling big data, real-world and remote monitoring applications) are welcome. In particular, bespoke techniques for enhanced data analytics (i.e., non-linear, linear, machine learning, artificial intelligence) and nuanced interpretation (i.e., multi-segment or multi-system co-ordination, interrogation of multimodal and multivariate datasets) are encouraged.

Dr. Javad Sarvestan
Dr. Lisa Alcock
Guest Editors

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• biomechanics
• human movement
• sports science
• gait analysis
• linear methods
• nonlinear methods
• machine learning
• artificial intelligence
• athletic performance
• injury prevention
• rehabilitation
• wearable sensors
• data-driven insights