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

Abstract

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.

Maximal Fully Tethered Swim Performance in Para Swimmers With Physical Impairment

“…It appears these swimmers have reduced limb length and surface area that predominately impacts their ability to generate propulsive forces during swimming, rather than causing increased active or passive drag. 23 Comparatively, there were lower coefficients of determination reported for Para swimmers with impaired muscle power (adj. R 2 = .63 to .70, p < .001) and hypertonia (adj.…”

A development framework for decision support systems in high-performance sport

“…In sport, DSS have been used for purposes such as scheduling optimization (S. Robertson & Joyce, 2018;S. J. Robertson & Joyce, 2015), sport-modality classification (Hogarth, Payton, Van de Vliet, Connick, & Burkett, 2018), skill/movement evaluation and classification (Clermont, Osis, Phinyomark, & Ferber, 2017;Kovalchik & Reid, 2018;Novatchkov & Baca, 2013;Pernek, Kurillo, Stiglic, & Bajcsy, 2015;Richter, King, Falvey, & Franklyn-Miller, 2018;Rindal, Seeberg, Tjonnas, Haugnes, & Sandbakk, 2017;Whiteside, Cant, Connolly, & Reid, 2017;Woods, Veale, Fransen, Robertson, & Collier, 2018;Wundersitz et al, 2015), assessing decision-making and motor control (Maselli et al, 2017), talent identification and team selection (M. Lai, Meo, Schifanella, & Sulis, 2018;B Ofoghi, Zeleznikow, Macmahon, & Dwyer, 2013;Taha, Musa, Abdul Majeed, Alim, & Abdullah, 2018;Woods et al, 2018;Xie, Xu, Nie, & Nie, 2017), biomechanical analysis (Bertani, Cappello, Benedetti, Simoncini, & Catani, 1999;Ertelt, Solomonovs, & Gronwald, 2018;Kianifar, Lee, Raina, & Kulic, 2016;Kipp, Giordanelli, & Geiser, 2018;Richter et al, 2018), assessing injury risk (Carey et al, 2018;Li, Huang, Wang, Yu, & Ao, 2016;Lopez-Valenciano et al, 2018;Rossi et al, 2018;Ruddy et al, 2018;Thornton, Delaney, Duthie, & Dascombe, 2017) & Robertson, 2017;Jaspers et al, 2018;Nagata et al, 2016), or assessing fatigue…”

The classification in Para swimming: Analysis of a Paralympic champion’s withdraw case

“…While some studies demonstrated the impact of the impairment on swimming performance 4 and race pace strategies, 5 others tested and proposed the implementation of quantitative measures and new methods into the classification process. 4,6–9 Regarding the physical impairment classification, Oh et al. 6 analyzed the normalized passive drag and verified an inconsistent difference between adjacent classes, and high within-class variability in the lower ones.…”

“…Hogarth et al. 7 investigated the impact of limb impairment on 100 m freestyle performance and provided insights to improve the definition of athletes’ classes through anthropometric parameters. Finally, Hogarth et al.…”

“…3 We acknowledge the difficulty in improving between-classifiers and between-assessments (physical and technical) agreement, but commercially available technological resources can be helpful if incorporated into the classification process. The use of quantitative measurements were proposed previously, 4,6–9 but has not been introduced in the classification process so far.…”