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Sports injuries are becoming increasingly widespread, and professional player injuries are having a negative impact on the field of sports. Preventing sports injuries is becoming more popular. Numerous machine learning (ML) techniques have been used in different sports injury fields since the birth of ML. In order to deal with the issue of karate injury treatment, rehabilitation, and prevention, this paper presents a new behavioral system to identify injuries and the rehabilitation process in karate utilizing hybrid models that mix unsupervised learning and supervised learning. In our scenario, we picked Autoencoder for unsupervised learning and CNN and DNN models for supervised learning. The experimental investigation shows that the suggested model is capable of yielding accurate outcomes. In fact, our model’s accuracy for DNN and CNN is 99.67% and 99.66%, respectively.

Behavioral System to Detect Injury and Rehabilitation Process in Karate Using Hybrid Model