Human activity recognition based on CSI in multiple scenarios

Xiaolin Zhang

doi:10.1117/12.3006733

10 October 2023 Human activity recognition based on CSI in multiple scenarios

Xiaolin Zhang

Proceedings Volume 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023); 127992O (2023) https://doi.org/10.1117/12.3006733
Event: 3rd International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 2023, Kuala Lumpur, Malaysia

Abstract

Due to the popularity of commercial WiFi devices prompting the use of WiFi devices to achieve indoor human activity recognition(HAR) has become possible, HAR plays an important role in human-computer interaction, virtual reality and meta-universe, human walking, running and other activities will have an impact on the propagation of WiFi signals, by analyzing the information of the affected channel state, WiFi-based HAR can be achieved. In this paper, human activity states of three environments are classified, firstly by Hampel filtering to remove the anomaly noise, after that by DWT to further reduce the noise interference, then by extracting the statistical features in the time-frequency domain, and finally by random forest classification to complete the classification recognition. Through experimental verification, the method proposed in this paper can achieve 92% and 91% recognition rate in laboratory scene and corridor scene, which is better than the traditional algorithm recognition rate. It can also achieve 89% accurate recognition rate in non-line-of-sight(NLOS) environment, which also confirms the robustness of the proposed algorithm to the environment.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xiaolin Zhang "Human activity recognition based on CSI in multiple scenarios", Proc. SPIE 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 127992O (10 October 2023); https://doi.org/10.1117/12.3006733

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