ComplexBeat: Breathing Rate Estimation from Complex CSI

TL;DR

This paper introduces ComplexBeat, a WiFi-based system that estimates breathing rates by analyzing channel impulse responses and applying calibration techniques to improve accuracy, demonstrating effective real-world performance.

Contribution

It proposes a novel approach using delay domain CSI and calibration methods for more accurate breathing rate estimation from WiFi signals.

Findings

Effective breathing rate estimation demonstrated

Calibration methods improve CSI data quality

System works reliably in real environments

Abstract

In this paper, we explore the use of channel state information (CSI) from a WiFi system to estimate the breathing rate of a person in a room. In order to extract WiFi CSI components that are sensitive to breathing, we propose to consider the delay domain channel impulse response (CIR), while most state-of-the-art methods consider its frequency domain representation. One obstacle while processing the CSI data is that its amplitude and phase are highly distorted by measurement uncertainties. We thus also propose an amplitude calibration method and a phase offset calibration method for CSI measured in orthogonal frequency-division multiplexing (OFDM) multiple-input multiple-output (MIMO) systems. Finally, we implement a complete breathing rate estimation system in order to showcase the effectiveness of our proposed calibration and CSI extraction methods.