Contactless Respiration Monitoring Via Off-the-Shelf WiFi Devices

Xuefeng Liu, Jiannong Cao, Shaojie Tang, Jiaqi Wen, Peng Guo

Research output: Journal article publicationJournal articleAcademic researchpeer-review

101 Citations (Scopus)

Abstract

Non-invasive human sensing based on radio signals has attracted numerous research interests in recent years. Previous work mainly focused on detecting the presence of a person or identifying human gestures and activities. In this paper, we show that with off-the-shelf WiFi devices, fine-grained respiration information of a person under different sleeping positions can be extracted successfully. We do this by introducing a breath monitoring system based on WiFi signals. This system adopts off-the-shelf WiFi devices to continuously collect the fine-grained wireless channel state information (CSI) around a person. From the CSI, the rhythmic patterns associated with respiration and abrupt changes due to the body movement are identified. Compared to existing respiration monitoring systems that usually require special devices attached to human body, this system is completely contactless. In addition, different from many vision-based sleep monitoring systems, it is robust to low-light environments and does not raise privacy concerns. Preliminary testing results show that our system can reliably track a person's respiration reliably in different sleeping postures.
Original languageEnglish
Article number7345587
Pages (from-to)2466-2479
Number of pages14
JournalIEEE Transactions on Mobile Computing
Volume15
Issue number10
DOIs
Publication statusPublished - 1 Oct 2016

Keywords

  • Breath detection
  • channel state information
  • Wireless technology

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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