Musculoskeletal Science & Sports Medicine Research Centre, Manchester Metropolitan University, Manchester, UK.
School of Health and Behavioural Sciences, University of the Sunshine Coast, Sunshine Coast, Australia.
J Sports Sci. 2021 Aug;39(sup1):62-72. doi: 10.1080/02640414.2021.1935114. Epub 2021 Jun 5.
The current protocol for classifying Para swimmers with hypertonia, ataxia and athetosis involves a physical assessment where the individual's ability to coordinate their limbs is scored by subjective clinical judgment. The lack of objective measurement renders the current test unsuitable for evidence-based classification. This study evaluated a revised version of the Para swimming assessment for motor coordination, incorporating practical, objective measures of movement smoothness, rhythm error and accuracy. Nineteen Para athletes with hypertonia and 19 non-disabled participants performed 30 s trials of bilateral alternating shoulder flexion-extension at 30 bpm and 120 bpm. Accelerometry was used to quantify movement smoothness; rhythm error and accuracy were obtained from video. Para athletes presented significantly less smooth movement and higher rhythm error than the non-disabled participants (p < 0.05). Random forest algorithm successfully classified 89% of participants with hypertonia during out-of-bag predictions. The most important predictors in classifying participants were movement smoothness at both movement speeds, and rhythm error at 120 bpm. Our results suggest objective measures of movement smoothness and rhythm error included in the current motor coordination test protocols can be used to infer impairment in Para swimmers with hypertonia. Further research is merited to establish the relationship of these measures with swimming performance.
目前针对痉挛型、共济失调型和手足徐动型脑瘫运动员的分类方案涉及身体评估,通过主观临床判断对个体协调四肢的能力进行评分。由于缺乏客观测量,目前的测试方法不适合基于证据的分类。本研究评估了改良的脑瘫游泳运动协调评估,纳入了运动平滑度、节奏误差和准确性的实用客观测量。19 名痉挛型脑瘫运动员和 19 名非残疾参与者进行了 30 秒双侧交替肩屈伸运动,频率为 30 bpm 和 120 bpm。加速度计用于量化运动平滑度;视频获得节奏误差和准确性。与非残疾参与者相比,脑瘫运动员的运动平滑度显著降低,节奏误差更高(p < 0.05)。随机森林算法在袋外预测中成功分类了 89%的痉挛型脑瘫运动员。在分类参与者时最重要的预测因子是两种运动速度下的运动平滑度,以及 120 bpm 的节奏误差。我们的结果表明,改良的运动协调测试方案中纳入的运动平滑度和节奏误差的客观测量可以用于推断痉挛型脑瘫游泳运动员的运动障碍。需要进一步的研究来确定这些措施与游泳表现的关系。