%0 Journal Article
%A CHEN Hai-ming
%A LIU Xi-wen
%T A Human Action Counting and Recognition Method Based on CSI
%D 
%R 10.13190/j.jbupt.2020-040
%J Journal of Beijing University of Posts and Telecommunications
%P 105-111
%V 43
%N 5
%X Nowadays WiFi channel state information is widely applied in passive(unobtrusive)human continuous activity recognition. The article uses commercial off-the-shelf devices and proposes a human action counting and recognition (Wi-ACR) method, based on channel state information(CSI). Wi-ACR takes advantage of the threshold algorithm and action indicator to detect the start and end time of a set of continuous actions,and then counts the number of actions through the peak-find algorithm and determines the start and end time of each action. After that,Wi-ACR takes the waveform-feature-based action recognition model and the statistical-feature-based action recognition model to obtain action recognition results respectively. Experiments show that Wi-ACR can achieve action counting accuracy of 95% and recognition accuracy of 90% with these two recognition models,in the scenarios with two types of actions(i.e. squat and walk)occurring simultaneously.
%U https://journal.bupt.edu.cn/EN/10.13190/j.jbupt.2020-040