ComplexBeat: Breathing Rate Estimation from Complex CSI

Sitian Li, Andreas Toftegaard Kristensen, A. Burg, Alexios Balatsoukas-Stimming
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引用次数: 2

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.
ComplexBeat:从复杂CSI中估计呼吸频率
在本文中,我们探索了使用来自WiFi系统的信道状态信息(CSI)来估计房间中人的呼吸频率。为了提取对呼吸敏感的WiFi CSI组件,我们建议考虑延迟域信道脉冲响应(CIR),而大多数最先进的方法考虑其频域表示。在处理CSI数据时的一个障碍是其振幅和相位受到测量不确定性的高度扭曲。因此,我们还提出了正交频分复用(OFDM)多输入多输出(MIMO)系统测量CSI的幅度校准方法和相位偏移校准方法。最后,我们实现了一个完整的呼吸频率估计系统,以展示我们提出的校准和CSI提取方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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