Title: Research on human health status recognition based on association algorithm

Authors: Taiping Jiang; Zhibing Wang; Lei Huang

Addresses: Xiangzhong Normal College for Preschool Education, Shaoyang, 422000, China ' School of Computer Science, Hunan University of Technology, Zhuzhou, 412007, China; Hunan Key Laboratory of Intelligent Information Perception and Processing Technology, Hunan University of Technology, Zhuzhou, 412007, China ' Xiangzhong Normal College for Preschool Education, Shaoyang, 422000, China

Abstract: A human health status recognition method based on association algorithm is proposed to address the problems of low recognition accuracy, low correlation of health data collection, and long recognition time in existing human health status recognition methods. Firstly, a temperature sensor is used to collect human body temperature data. Secondly, the photoelectric capacitance method is used to collect heart rate and blood oxygen data. Once again, by setting the 3D coordinate system of human bone points and using the depth image coordinate system to determine the true distance of bone points, the collection of human bone related data is achieved. Finally, association algorithms are used to analyse the relationship between human health status data. Once a human health status recognition function is constructed, the recognition of health status is then completed. The test results show that the accuracy of the proposed method for identifying human health status remains around 99%.

Keywords: association algorithm; identification of human health status; body temperature data; bone data; identification function.

DOI: 10.1504/IJDMB.2023.134292

International Journal of Data Mining and Bioinformatics, 2023 Vol.27 No.4, pp.267 - 278

Received: 13 Apr 2023
Accepted: 19 Jun 2023
Published online: 17 Oct 2023 *