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Sports wearable monitoring equipment is an intelligent device that collects many physiological signals of the human body through multiple sensors. It has a very active role in promoting data testing in the field of sports. This article is aimed at studying the impact of sports wearable detection devices based on vision sensors on the sports industry and at proposing effective strategies for the development of sports wearable devices in the sports industry. This paper proposes an azimuth integration algorithm based on wearable sensor data. This goal establishes a new feature based on azimuth angle information for a reliable human behavior recognition system based on acceleration data. Based on summarizing and comparing the advantages and disadvantages of existing azimuth conversion algorithms, this paper develops an azimuth code conversion algorithm based on the combination of additional processing and Kalman processing to explore the impact of wearable devices on the sports industry. The experimental results of this article show that in the current sports industry, more than 19.74 million sports wearable testing devices have been put into use normally, which also means that the industry is about to enter a significant stage of development.

Impact of Sports Wearable Testing Equipment Based on Vision Sensors on the Sports Industry