Human motion recognition based on passive RFID and multi-model fusion

Xu Yang; Wenchao Luo; Xiaofeng An

doi:10.1117/12.2685530

28 July 2023 Human motion recognition based on passive RFID and multi-model fusion

Xu Yang, Wenchao Luo, Xiaofeng An

Proceedings Volume 12716, Third International Conference on Digital Signal and Computer Communications (DSCC 2023); 127160A (2023) https://doi.org/10.1117/12.2685530
Event: Third International Conference on Digital Signal and Computer Communications (DSCC 2023), 2023, Xi'an, China

Abstract

Aiming at the problems that the human motion recognition method based on machine vision and sensors is easy to reveal user privacy and inconvenient to carry, this paper proposes a human motion recognition method based on passive RFID and multi-model fusion. By wearing a flexible liquid metal tag on the human body, the effect of different actions on the RSSI signal of the receiver is utilized, The approximate component and detail component of the signal extracted by wavelet transform are used as fusion features to represent human motion, and the four models of KNN, DT, SVM and LR are fused to construct the Blending model with KNN, DT and SVM as primary learners and LR as secondary learners for motion recognition. The experiments show that the accuracy of the Blending model for the five movements of standing, sitting, walking, running and falling is 97.29%, Compared with individual learners, it has better recognition effect and greatly improves the convenience of human motion recognition.

Citation Download Citation

Xu Yang, Wenchao Luo, and Xiaofeng An "Human motion recognition based on passive RFID and multi-model fusion", Proc. SPIE 12716, Third International Conference on Digital Signal and Computer Communications (DSCC 2023), 127160A (28 July 2023); https://doi.org/10.1117/12.2685530

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