Identifying generalised segmental acceleration patterns that contribute to ground reaction force features across different running tasks

摘要: Abstract Objective To support future developments of field-based biomechanical load monitoring tools, this study aimed to identify generalised segmental acceleration patterns and their contribution ground reaction forces (GRFs) across different running tasks. Design Exploratory experimental design. Methods A multivariate principal component analysis (PCA) was applied a combination data from all body segments for fifteen team-sport athletes performing accelerated, decelerated constant low-, moderate- high-speed running, 90° cutting trials. Segmental profiles were then reconstructed each (PC) used calculate specific GRF contributions. Results The first PC explained 48.57% the variability primarily related between-task differences in overall magnitude impulse. Magnitude timing high-frequency features (i.e. impact characteristics) by second (12.43%) also revealed important differences. most characteristics five PCs, while PCs beyond that contained small contributions Conclusions These findings show PCA approach can reveal features, but relative importance activities are task dependent. Using assess whole-body loading generically various movements may thus require identification algorithms and/or advanced sensor or fusion approaches.