Wi-Fi sensing gesture control algorithm based on semi-supervised generative adversarial network.

ABSTRACT: A Wi-Fi-sensing gesture control system for smart homes has been developed based on a theoretical investigation of the Fresnel region sensing model, addressing the need for non-contact gesture control in household environments. The system collects channel state information (CSI) related to gestures from Wi-Fi signals transmitted and received by network cards within a specific area. The collected data undergoes preprocessing to eliminate environmental interference, allowing for the extraction of complete gesture sets. Dynamic feature extraction is then performed, followed by the identification of unknown gestures using pattern recognition techniques. An improved dynamic double threshold gesture interception algorithm is introduced, achieving a gesture interception accuracy of 98.20%. Further

SUBMITTER: Wang C 

PROVIDER: S-EPMC11623234 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature