A novel method to guide classification of para swimmers with limb deficiency

• Published in: Scandinavian journal of medicine & science in sports 2018-11, Vol.28 (11), p.2397-2406
• Main Authors: Hogarth, L., Payton, C., Vliet, P., Connick, M., Burkett, B.
• Format: Article
• Language: English
• Subjects: Classification; disability; freestyle; machine learning; paralympic; Paralympic Games; partial least squares; Swimming
• ISSN: 0905-7188; 1600-0838
• DOI: 10.1111/sms.13229

The International Paralympic Committee has directed International Federations that govern Para sports to develop evidence‐based classification systems. This study defined the impact of limb deficiency impairment on 100 m freestyle performance to guide an evidence‐based classification system in Para Swimming, which will be implemented following the 2020 Tokyo Paralympic games. Impairment data and competitive race performances of 90 international swimmers with limb deficiency were collected. Ensemble partial least squares regression established the relationship between relative limb length measures and competitive 100 m freestyle performance. The model explained 80% of the variance in 100 m freestyle performance and found hand length and forearm length to be the most important predictors of performance. Based on the results of this model, Para swimmers were clustered into four‐, five‐, six‐, and seven‐class structures using nonparametric kernel density estimations. The validity of these classification structures, and effectiveness against the current classification system, were examined by establishing within‐class variations in 100 m freestyle performance and differences between adjacent classes. The derived classification structures were found to be more effective than current classification based on these criteria. This study provides a novel method that can be used to improve the objectivity and transparency of decision‐making in Para sport classification. Expert consensus from experienced coaches, Para swimmers, classifiers, and sport science and medicine personnel will benefit the translation of these findings into a revised classification system that is accepted by the Para swimming community.