Biomechanical analysis and optimization of sports action training in virtual reality (VR) environment

Over the past years, virtual reality (VR) has become much more popular. VR combines several technologies to provide an immersive digital environment. This environment allows users to engage and react to their actions, creating a virtual world where users feel more present. In biomechanical analysis, researchers analyze the physical characteristics of biological tissues and model the relationship between tissue form and function. Utilizing VR headsets, motion-tracking apparatus, and realistic virtual worlds that simulate actual sports situations are all part of virtual sports training. VR lacks realism, which can be related to the absence of sensory input, making it unsuitable for training fine motor skills. The research aims to perform biomechanical analysis and optimize sports action training inside a VR setting. A mountain gazelle optimizer fine-tuned adjustable convolution neural network (MGO-ACNN) is proposed to examine the joint angle selections utilized by sports action. In this study, human motion image data are utilized to capture various angles of the training action. The data was preprocessed using a Wiener Filter (WF) for the obtained data. Analyzing spatial frequency and orientation in images for feature extraction is accomplished using the Gabor Filter (GF). This approach incorporates VR simulations to provide a more regulated and immersive setting for joint angle analysis during sports training. The proposed method is implemented using Python software. The result demonstrated by the proposed method significantly outperforms the existing algorithms. The performance parameters for accuracy (99.73%), precision (99.75%), recall (99.73%), and F1-score (99.72%) are assessed in this study. The VR experiments indicate that optimal sports preparation involves a sports action while maintaining a batting speed consistent with the joint to lower the center of gravity. This research highlights the more effective, personalized sports training system, leveraging VR to simulate real-world conditions while providing detailed biomechanical insights.