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Vital Sign and Sleep Monitoring Using Millimeter Wave

Published: 24 April 2017 Publication History

Abstract

Continuous monitoring of human’s breathing and heart rates is useful in maintaining better health and early detection of many health issues. Designing a technique that can enable contactless and ubiquitous vital sign monitoring is a challenging research problem. This article presents mmVital, a system that uses 60GHz millimeter wave (mmWave) signals for vital sign monitoring. We show that the mmWave signals can be directed to human’s body and the Received Signal Strength (RSS) of the reflections can be analyzed for accurate estimation of breathing and heart rates. We show how the directional beams of mmWave can be used to monitor multiple humans in an indoor space concurrently. mmVital also provides sleep monitoring with sleeping posture identification and detection of central apnea and hypopnea events. It relies on a novel human finding procedure where a human can be located within a room by reflection loss-based object/human classification. We evaluate mmVital using a 60GHz testbed in home and office environment and show that it provides the mean estimation error of 0.43 breaths per minute (Bpm; breathing rate) and 2.15 beats per minute (bpm; heart rate). Also, it can locate the human subject with 98.4% accuracy within 100ms of dwell time on reflection. We also demonstrate that mmVital is effective in monitoring multiple people in parallel and even behind a wall.

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Published In

cover image ACM Transactions on Sensor Networks
ACM Transactions on Sensor Networks  Volume 13, Issue 2
May 2017
235 pages
ISSN:1550-4859
EISSN:1550-4867
DOI:10.1145/3081318
  • Editor:
  • Chenyang Lu
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 24 April 2017
Accepted: 01 February 2017
Revised: 01 February 2017
Received: 01 April 2016
Published in TOSN Volume 13, Issue 2

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Author Tags

  1. 60 GHz
  2. Millimeter wave
  3. healthcare
  4. human finding
  5. signal reflection and blockage
  6. smart home
  7. vital signs

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  • (2025)Inclusive Role of Internet of (Healthcare) Things in Digital Health: Challenges, Methods, and Future DirectionsGenerative Artificial Intelligence for Biomedical and Smart Health Informatics10.1002/9781394280735.ch12(239-258)Online publication date: 3-Jan-2025
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