A Survey of Wireless Sensing Human Posture Recognition Research

DOI

10.2991/978-94-6463-986-5_32How to use a DOI?

Keywords

Wireless sensing; Human posture recognition; Millimeter-wave radar; Through-wall radar; WiFi signals

Abstract

With the development of human-computer interaction, virtual reality, and other fields, the importance of human posture estimation technology is becoming increasingly prominent. Traditional optical methods are limited by light, occlusion, and privacy issues, whereas wireless sensing techniques have become a core research direction owing to their non-invasiveness and environmental robustness. In this study, nine cutting-edge wireless sensing technologies based on millimeter-wave radar, through-wall radar, and WiFi signals were analyzed in terms of hardware suitability, signal processing frameworks, and deep learning model optimization strategies. Millimeter-wave radar technology forms a technological divide between accuracy, light weight, and multi-person robustness, whereas through-wall radar focuses on the balance between accuracy and generalization ability in walled scenarios, and WiFi signals show unique value in the smart home and security fields. The study points out that current technology faces challenges such as signal sparsity, insufficient cross-modal generalization, and high hardware cost, and explores typical application scenarios such as medical, healthcare, and industrial security. Future research can focus on self-supervised multimodal fusion, privacy-preserving frameworks, and dynamic adaptive algorithms, laying the technical foundation for 6G communication-sensing integration.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Zihan Qi
PY  - 2026
DA  - 2026/02/18
TI  - A Survey of Wireless Sensing Human Posture Recognition Research
BT  - Proceedings of the 2025 International Conference on Electronics, Electrical and Grid Technology (ICEEGT 2025)
PB  - Atlantis Press
SP  - 294
EP  - 306
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-986-5_32
DO  - 10.2991/978-94-6463-986-5_32
ID  - Qi2026
ER  -