IntroductionAccurately predicting the competitive performance of elite athletes is an essential prerequisite for formulating competitive strategies. Women’s all-around speed skating event consists of four individual subevents, and the competition system is complex and challenging to make accurate predictions on their performance.ObjectiveThe present study aims to explore the feasibility and effectiveness of machine learning algorithms for predicting the performance of women’s all-around speed skating event and provide effective training and competition strategies.MethodsThe data, consisting of 16 seasons of world-class women’s all-around speed (...) skating competition results, used in the present study came from the International Skating Union. According to the competition rules, distinct features are filtered using lasso regression, and a 5,000 m race model and a medal model are built using a fivefold cross-validation method.ResultsThe results showed that the support vector machine model was the most stable among the 5,000 m race and the medal models, with the highest AUC. Furthermore, 3,000 m points are the main characteristic factors that decide whether an athlete can qualify for the final. The 11th lap of the 5,000 m, the second lap of the 500 m, and the fourth lap of the 1,500 m are the main characteristic factors that affect the athlete’s ability to win medals.ConclusionCompared with logistic regression, random forest, K-nearest neighbor, naive Bayes, neural network, support vector machine is a more viable algorithm to establish the performance prediction model of women’s all-around speed skating event; excellent performance in the 3,000 m event can facilitate athletes to advance to the final, and athletes with outstanding performance in the 500 m event are more likely competitive for medals. (shrink)

ObjectiveThe studies showed the benefits of virtual reality training for functional mobility and balance in older adults. However, a large variance in the study design and results is presented. We, thus, completed a systematic review and meta-analysis to quantitatively examine the effects of VRT on functional mobility and balance in healthy older adults.MethodsWe systematically reviewed the publications in five databases. Studies that examine the effects of VRT on the measures of functional mobility and balance in healthy older adults were screened (...) and included if eligible. Subgroup analyses were completed to explore the effects of different metrics of the intervention design on those outcomes related to functional mobility and balance.ResultsFifteen studies of 704 participants were included. The quality of these studies was good. Compared to traditional physical therapy, VRT induced greater improvement in TUG and one-leg stance with open eyes. Subgroup analyses revealed that immersive VRT with more than 800 min of total intervention time over 8 weeks and at least 120 min per week and/or designed by the two motor-learning principles was optimal for functional mobility and balance.ConclusionVirtual reality training can significantly improve functional mobility and balance in healthy older adults compared to TPT, and the findings provided critical knowledge of the optimized design of VRT that can inform future studies with more rigorous designs.Systematic Review Registration[https://www.crd.york.ac.uk/PROSPERO/], identifier [CRD42021297085]. (shrink)

BackgroundRecently, considerable research has been conducted to study the effects of traditional Chinese exercises on cognitive function in older adults with MCI. We completed a comprehensive systematic review and meta-analysis to assess the efficacy of TCEs on cognitive function in this population.MethodsA search strategy based on the PICOS principle was used to find the literatures in the databases of PubMed, Web of Science, MEDLINE, SPORT-Discus, PsycINFO, Cochrane Central Register of Controlled Trials, Ovid. The quality and risk of bias in the (...) studies were independently assessed by two researchers.ResultsNine trials with 1,290 participants were included. The effect size of TCEs on global cognitive function was small when compared to the active control and was moderate compared to the inactive control; statistically significant effects were also found for short-term memory, long-term memory, shifting, language ability, visuospatial perception.ConclusionThis meta-analysis provides clinicians with moderate evidence to recommend that TCEs hold potential to enhance both global cognitive function and multiple domains of cognitive function, which, however, needs to be confirmed and further examined in futures studies. The results of this work provide critical knowledge for the design of future studies implementing TCEs as well as its clinical practice. Future RCTs with rigorous designs are needed to help obtain more definitive conclusions on the effects of TCEs on cognitive function in older adults with MCI. (shrink)