Improvement of Traditional Electrical Engineering System Based on Statistical Theory

In the domain of conventional wearable devices, many action judgments rely on expert experience for classification. This is not conducive to the promotion of experience, and also puts forward higher requirements on the professional skills of experts. Based on this, this paper optimizes and ebhances the field of wearable devices based on statistical methods, and proposes a feature-based action skill recognition model based on feature statistical analysis. After testing, the electrical engineering equipment improved in the case of the statistical model proposed in this paper has higher professional skill recognition accuracy and stronger generalization ability, which can provide a reliable analysis basis for wearable devices in single ball sports.