Research and Analysis of Behavioral Gesture Recognition Technology Based on Wireless Perception

With the rapid development and continuous progress of wireless communication technology, the role played by wireless perception technology in the field of behavior and gesture recognition has become increasingly important and prominent.Therefore, this paper summarizes several current behavior and attitude recognition technologies based on wireless perception and systematically combs and analyzes them.It is found that the recognition accuracy of CeHAR is higher than that of the best recognition method before.AFEE-MatNet can significantly shorten the training time and address the limitations of retrained models using Wi-Fi CSI data in new environments.CNN-ABLSTM achieves high recognition accuracy in a variety of environments.The average accuracy of DPWiT for the localization of the start and end time and category of the activity far exceeds that of the baseline model.WiPhase reduces the computational complexity and the number of model parameters.Therefore, the above methods can be flexibly selected according to the performance requirements of different application scenarios.