Description

Gait recognition identifies or verifies a walking subject from the periodic Doppler signature their stride imparts on a CSI stream. Unlike camera-based gait, the WiFi version sees through clothing and lighting, capturing torso-Doppler fundamental plus limb-Doppler harmonics. WifiU (Wang et al.) defined the canonical pipeline: bandpass filter → spectrogram → cycle extraction → classifier.

When it's used

  • Identity-aware occupancy
  • Authentication via behavioural biometrics
  • Health monitoring (gait deterioration, Parkinsonian signatures)
  • As a sub-task of human-activity-recognition

Limitations

  • Susceptible to walking-speed variation and footwear changes
  • Limited robustness to direction of walk relative to TX/RX baseline
  • Carry-state (bag, child) shifts the Doppler signature

Source Papers

  • wang2016_6482 — WifiU canonical CSI gait pipeline
  • ahmad2024_8639 — gait classification on CSI
  • wang2026_2758 — recent gait-aware sensing
  • zabin2026_a20c — current gait benchmark

3 vault papers use this method

Titles and DOIs only — no abstracts, no analyses.

  • Gait recognition using wifi signals 2016 DOI ↗
  • Cross-Domain WiFi Sensing with Channel State Information: A Survey 2023 DOI ↗
  • A CSI Dataset for Wireless Human Sensing on 80 MHz Wi-Fi Channels 2023 DOI ↗