Sub-field · 6 papers
WiFi CSI Gesture Sensing
Wi-Fi Channel State Information (CSI) sensing for human activity recognition—including gesture recognition, multi-person detection, and behavioral monitoring—forms the core focus, with methods ranging from deep learning (graph neural networks, lightweight models) to systematic empirical evaluation. Research addresses practical challenges such as cross-domain generalization, energy efficiency, and the fundamental capabilities and limitations of CSI-based sensing on modern wide-band (80 MHz) channels. One paper on cognitive-aware user search behavior simulation appears tangential but may relate to human behavior modeling more broadly.
Papers in this community
- A CSI Dataset for Wireless Human Sensing on 80 MHz Wi-Fi Channels 2023 DOI ↗
- MUSE-Fi: Contactless MUti-person SEnsing Exploiting Near-field Wi-Fi Channel Variation 2023 DOI ↗
- Exposing the CSI: A Systematic Investigation of CSI-based Wi-Fi Sensing Capabilities and Limitations 2023 DOI ↗
- A Survey on Green Wireless Sensing: Energy-Efficient Sensing via WiFi CSI and Lightweight Learning 2026 DOI ↗
- Cognitive-Aware User Search Behavior Simulation 2024 DOI ↗
- WiGNN: WiFi-Based Cross-Domain Gesture Recognition Inspired by Dynamic Topology Structure 2024 DOI ↗