A1356
Title: Statistical inferences from biomechanical fatigue data of running athletes
Authors: Rupsa Basu - University of Cologne (Germany) [presenting]
Abstract: Statistical methodologies relevant to the study of biomechanical fatigue data from runners are explored. In particular, the focus is on the hip, knee and ankle angle data collected from both novice as well as experienced runners during a fatiguing protocol. In the biomechanical world, it is understood that fatigue induces specific changes in the movement of these joints during the course of the run. These changes are a consequence of the body adjusting to tiring conditions. Some of these adaptations of the body may, however, result in long-term injuries. It is, therefore, essential to detect these changes and make appropriate adjustments to the training strategies. In this regard, various statistical methodologies developed specifically for this data example are assessed. From the statistical aspect, relevant size change point detection for functional data is studied. The methodologies developed therein contribute to retrospective change analysis of biomechanical data. Further, online change analysis is also studied using a martingale statistic to enable biomechanical scientists to study real-time fatigue while the athlete is still running. Overall, it is shown how the methods presented provide biomechanical scientists and sports trainers with methodologies to understand the individual movement patterns of running athletes.
