Determination of subset models for predicting vertical centre of mass position during front crawl in male swimmers

ABSTRACT

We attempted to find a subset model that would allow robust prediction of a swimmer’s vertical body position during front crawl with fewer markers, which can reduce extra drag and time-consuming measurements. Thirteen male swimmers performed a 15-metre front crawl either with three different lung-volume levels or various speeds, or both, without taking a breath with 36 reflective markers. The vertical positions of the centre of mass (CoM) and four representative landmarks in the trunk segment over a stroke cycle were calculated using an underwater motion-capture system. We obtained 212 stroke cycles across trials and analysed the vertical position derived from 15 patterns as candidates for the subset models. Unconstrained optimisation minimises the root-mean-square error between the vertical CoM position and each subset model. The performance evaluated from the intra-class correlation coefficient (ICC) and weight parameters of each subset model were detected from the mean values across five-fold cross-validation. The subset model with four markers attached to the trunk segment showed good reliability (ICC: 0.776 ± 0.019). This result indicates that the subset model with few markers can robustly predict a male swimmer’s vertical CoM position during front crawl under a wide range of speeds from 0.66 to 1.66 m · s⁻¹.

KEYWORDS:

• Underwater motion-capture system
• body position
• simple model
• intra-class correlation coefficient
• swimming

Acknowledgments

We thank Prof. Hiroaki Kanehisa (National Institute of Fitness and Sports in Kanoya) and Prof. Glen Lichtwark (The University of Queensland) for their helpful suggestions. We thank Dr Yu Miyawaki (National Institute of Advanced Industrial Science and Technology) for his advice on statistical analysis. We also thank Mr Tomoya Kaji (National Institute of Fitness and Sports in Kanoya) and Mr Ryosei Suzuki (Shinshu University) for their assistance with the experiments.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the JSPS KAKENHI under Grant number [JP20K14686] and Yamaha Motor Foundation for Sports.