The Integration of Personalized Training Program Design and Information Technology for Athletes

Abstract

In order to integrate the training of athletes with information technology, this paper proposes a method for evaluating the performance of athletes using training technology. HR, O2, and hemoglobin were selected as input vectors of SVM, and the corresponding values were used as outputs to generate the training model. Adjust the support vector machine to minimize measurement error based on the learning objective. Support vector machines are used to study training patterns and develop model to evaluate athletes’ performance. College athletes were taken as research subjects and the effects of training were examined in five sports: football, basketball, basketball, swimming, and running. The results show that the relative error of this type is less than 1 when measuring the performance of various sports subjects; Relative errors in measuring the academic performance of athletes in various sports using physical fitness standards and sport-specific skills 1. The proposed model proves that the athlete’s training index is incorrect and has a useful application.