Sports Injury Forecasting and Complexity: A Synergetic Approach
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Sports Injury Forecasting and Complexity: A Synergetic Approach Sergio T. Fonseca1 · Thales R. Souza1 · Evert Verhagen2,3 · Richard van Emmerik4 · Natalia F. N. Bittencourt5 · Luciana D. M. Mendonça6 · André G. P. Andrade7 · Renan A. Resende1 · Juliana M. Ocarino1
© Springer Nature Switzerland AG 2020
Abstract The understanding that sports injury is the result of the interaction among many factors and that specific profiles could increase the risk of the occurrence of a given injury was a significant step in establishing programs for injury prevention. However, injury forecasting is far from being attained. To be able to estimate future states of a complex system (forecasting), it is necessary to understand its nature and comply with the methods usually used to analyze such a system. In this sense, sports injury forecasting must implement the concepts and tools used to study the behavior of self-organizing systems, since it is by self-organizing that systems (i.e., athletes) evolve and adapt (or not) to a constantly changing environment. Instead of concentrating on the identification of factors related to the injury occurrence (i.e., risk factors), a complex systems approach looks for the high-order variables (order parameters) that describe the macroscopic dynamic behavior of the athlete. The time evolution of this order parameter informs on the state of the athlete and may warn about upcoming events, such as injury. In this article, we describe the fundamental concepts related to complexity based on physical principles of self-organization and the consequence of accepting sports injury as a complex phenomenon. In the end, we will present the four steps necessary to formulate a synergetics approach based on self-organization and phase transition to sports injuries. Future studies based on this experimental paradigm may help sports professionals to forecast sports injuries occurrence.
* Sergio T. Fonseca [email protected] 1
Graduate Program in Rehabilitation Sciences, Physical Therapy Department, and Centro de Treinamento Esportivo, Universidade Federal de Minas Gerais, 6627, Pampulha, 31270‑901 Belo Horizonte, MG, Brazil
2
Amsterdam Collaboration on Health & Safety in Sports, Department of Public and Occupational Health, Amsterdam Movement Sciences, Amsterdam UMC, Amsterdam, Netherlands
3
Graduate Program in Rehabilitation Science, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
4
Motor Control Laboratory, Department of Kinesiology, University of Massachusetts Amherst, Amherst, MA 01003, USA
5
Uni-BH University, Belo Horizonte, MG, Brazil
6
Physical Therapy Department, Universidade Federal dos Vales do Jequitinhonha e Mucuri, Diamantina, MG, Brazil
7
Graduate Program in Sports Sciences, Sports Department, and Centro de Treinamento Esportivo, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil
Key Points The forecasting of sports injury requires the use of a synergetics approach based on principles of self-organization and phase transition in
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