A Field-Based Approach to Determine Soft Tissue Injury Risk in Elite Futsal Using Novel Machine Learning Techniques

被引:16
|
作者
Ruiz-Perez, Inaki [1 ]
Lopez-Valenciano, Alejandro [2 ]
Hernandez-Sanchez, Sergio [3 ]
Puerta-Callejon, Jose M. [4 ]
De Ste Croix, Mark [5 ]
Sainz de Baranda, Pilar [6 ]
Ayala, Francisco [7 ]
机构
[1] Miguel Hernandez Univ Elche, Dept Sport Sci, Sports Res Ctr, Elche, Spain
[2] King Juan Carlos Univ, Ctr Sport Studies, Madrid, Spain
[3] Miguel Hernandez Univ Elche, Dept Pathol & Surg, Physiotherapy Area, Alicante, Spain
[4] Univ Castilla La Mancha, Dept Comp Syst, Albacete, Spain
[5] Univ Gloucestershire, Sch Sport & Exercise, Gloucester, England
[6] Univ Murcia, Fac Sports Sci, Dept Phys Act & Sport, Murcia, Spain
[7] Univ Murcia, Fac Sports Sci, Dept Phys Act & Sport, Murcia, Spain
来源
FRONTIERS IN PSYCHOLOGY | 2021年 / 12卷
关键词
injury prevention; modeling; screening; decision-making; algorithm; decision tree; ECCENTRIC HAMSTRING STRENGTH; PROFESSIONAL SOCCER PLAYERS; ANTERIOR CRUCIATE LIGAMENT; BALANCE PERFORMANCE; DYNAMIC BALANCE; PREDICT INJURY; TRAINING-LOAD; STRAIN INJURY; FOOTBALL; CLASSIFICATION;
D O I
10.3389/fpsyg.2021.610210
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
Lower extremity non-contact soft tissue (LE-ST) injuries are prevalent in elite futsal. The purpose of this study was to develop robust screening models based on pre-season measures obtained from questionnaires and field-based tests to prospectively predict LE-ST injuries after having applied a range of supervised Machine Learning techniques. One hundred and thirty-nine elite futsal players underwent a pre-season screening evaluation that included individual characteristics; measures related to sleep quality, athlete burnout, psychological characteristics related to sport performance and self-reported perception of chronic ankle instability. A number of neuromuscular performance measures obtained through three field-based tests [isometric hip strength, dynamic postural control (Y-Balance) and lower extremity joints range of motion (ROM-Sport battery)] were also recorded. Injury incidence was monitored over one competitive season. There were 25 LE-ST injuries. Only those groups of measures from two of the field-based tests (ROM-Sport battery and Y-Balance), as independent data sets, were able to build robust models [area under the receiver operating characteristic curve (AUC) score >= 0.7] to identify elite futsal players at risk of sustaining a LE-ST injury. Unlike the measures obtained from the five questionnaires selected, the neuromuscular performance measures did build robust prediction models (AUC score >= 0.7). The inclusion in the same data set of the measures recorded from all the questionnaires and field-based tests did not result in models with significantly higher performance scores. The model generated by the UnderBagging technique with a cost-sensitive SMO as the base classifier and using only four ROM measures reported the best prediction performance scores (AUC = 0.767, true positive rate = 65.9% and true negative rate = 62%). The models developed might help coaches, physical trainers and medical practitioners in the decision-making process for injury prevention in futsal.
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页数:15
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