Biomechanical rehabilitation networks for student injuries at universities in central Mexico
DOI:
https://doi.org/10.62621/es9wt655Keywords:
Neural Network Analysis, Biomechanical Rehabilitation, Injury Risk, Rehabilitation TimeAbstract
Biomechanical rehabilitation has been established as an alternative to student injuries in universities, although adherence to rehabilitation has not been explored from the patient's perspective. Therefore, the objective of this work was to compare an observed neural network model with respect to the state of the art in order to anticipate rehabilitation scenarios. A cross-sectional, exploratory and correlational study was carried out with a sample of 450 students selected for their injury and biomechanical intervention in universities in central Mexico. The results indicate the prevalence of time as a structural and central axis in the learning sequence of the network. In relation to the state of the art where the rehabilitation context is highlighted, this work suggests the inclusion of objective variables in order to complement them with rehabilitation expectations to anticipate adherence scenarios.
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