Abstract

This study offers a novel mathematical approach to sports technique analysis and motor equivalency investigation. The method is aimed to deal with intensive interaction between the environment and a trainee, and activities for which imitation learning is less efficient and movements must be established individually. The free-fall stage of skydiving is investigated, when aerial manoeuvres are performed by changing the body posture and thus deflecting the surrounding airflow. The natural learning process of body flight is hard and protracted as the required movements are not similar to our natural movement repertoire, are often counter-intuitive, and highly dependant on anthropometric factors. The proposed method extracts the trainee’s movement patterns via Principal Component Analysis, and analyses the performed manoeuvres by modelling the dynamic response of the closed-loop feedback control system comprising the body actuated by each pattern and the environment. The method can provide a valuable insight into the subject’s learning process. The main novelty is that instead of comparing trainee’s movements to a template or a movement pattern, extracted from a top-rated athlete, we offer an independent way of technique analysis. Design tools of automatic control theory are utilised to suggest technique modifications that provide the desired performance improvement. An unconventional insight into the motor equivalence problem is achieved: Multiple body degrees-of-freedom are needed for shaping dynamic characteristics of the controlled plant. Movement patterns synergies provide a trade-off between these characteristics, e.g. stability and agility. The method is demonstrated on three case studies of aerial rotation of skilled, less-skilled, and elite skydivers.

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