Design and Practice of Aerobics Teaching Design Based on Data Fusion Algorithm

Abstract

Aerobic exercise is a very popular form of exercise. It combines various forms of sports and music. Aerobic exercise improves muscle tone and relaxes the mind and body while burning calories. It is designed to individualize instruction for different audiences. It is an important factor in the applicability of the operation. The purpose of this paper is to build different human models based on sensor network numbers to quantify different movements through the Internet of Things (IoT) to design personalized curriculum design and practice to improve the popularity of creative aerobics curriculum. In this paper, we first give an overview of the algorithm and data fusion algorithm and then simulate the aerobics creative curriculum design. First, the variance is used as the error measure to establish the data fusion algorithm and aerobics new concept innovation curriculum design and practice. The established model is compared with the aerobics curriculum design under the traditional model to highlight the advantages of the curriculum design under the data fusion algorithm. A comparison is also made with examples. The experimental results show that the data of the audience's movement changes during different creative processes solve the aerobics creative editing problem. Compared with the traditional curriculum design, the efficiency of the curriculum design and practice is improved by 20.23%.