Generation Algorithm of Personalized Sports Training Program Based on Sensor Data

Nowadays, people are paying more and more attention to their own physical health, and many teenagers will choose to take the path of being a sports student. Whether it is to improve their own health or to improve sports performance, everyone has individual differences, and there are also differences in what they pursue through exercise, the set of training programs cannot be suitable for everyone. Therefore, it is necessary to formulate personalized sports training programs for different people and different needs. The training plan that suits our own situation can not only ensure our own safety, prevent injuries during sports, but also improve the efficiency of progress. Based on this, this paper establishes a model by studying deep learning algorithms, recommendation algorithms and sensor data. The model can collect the data of people’s movement through the sensor, and then use the recommendation algorithm to analyze and process the sensor data to automatically generate a personalized sports training plan. Experiments have proved that the model based on sensor data designed in this paper combined with deep learning algorithms and recommendation algorithms can generate accurate and effective personalized sports training programs. In the experiment, the strength level of the experimenters trained using the training program generated by the model has improved, and the strength has increased by an average of 18kg within three months, and the weight and body fat rate have not changed much.