Intelligent anti-epidemic mask based on KF and ECF fusion algorithm

作     者：Xia, Kun Li, Xiang Li, Xueyong Liu, Yiren Zhang, Hongwei Hou, Ruifeng 

作者机构：Univ Shanghai Sci & Technol Dept Elect Engn Shanghai Peoples R China 

出 版 物：《ELECTRONICS LETTERS》 (电子学快报)

年 卷 期：2021年第57卷第19期

页      面：724-726页

核心收录：

学科分类：0808[工学-电气工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 

基　　金：National Natural Science Foundation of China Key Project of National Natural Science Foundation of China [51637001/E070701] 

主　　题：Filtering methods in signal processing Biomedical measurement and imaging Digital signal processing Biomedical engineering Biology and medical computing 

摘      要：In response to environmental pollution and the spread of Coronavirus Disease 2019 (COVID-19), this paper proposes a new type of smart mask design, and specifically proposes an optimized double closed-loop control method, especially an improved filtering fusion algorithm. Using the filtering fusion algorithm proposed in this paper, after the Kalman filter (KF) filters the raw data of the attitude sensor, explicit complementary filtering and data fusion are used to obtain the attitude angle of the body. At the same time, the obtained attitude angle is combined with acceleration and blood oxygen concentration to obtain the behaviour characteristic value. On this basis, the speed of the oxygen supply fan captured by the photoelectric sensor is used to form a closed loop with the characteristic value of the behaviour. Finally, the structure of the mask is upgraded and optimized through fluid mechanics simulation, and experiments have verified that the combination of the replaceable filter cloth, the intelligent control system and the ultraviolet disinfection device can effectively protect people s health.