Cited by 101Non-Invasive Vital Sign MonitoringWireless Body Area NetworksECG Monitoring and Analysis

Non-invasive respiration rate monitoring using a single COTS TX-RX pair

Kaltiokallio, Ossi, Yigitler, Huseyin, Jantti, Riku, Patwari, Neal·2014·IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks

Abstract

Respiratory rate is an important vital sign that can indicate progression of illness but to also predict rapid decline in health. For the purpose, non-contact monitoring systems are becoming more popular due to the self-evident increase in patient comfort. As a cost effective solution for non-invasive breathing monitoring, utilizing the received signal strength measurements of inexpensive transceivers has been proposed. However, the applicability of the available solutions is limited since they rely on numerous sensors. In this work, considerable improvement is made, and a respiratory rate monitoring system based on a single commercial off-the-shelf transmitter-receiver pair is presented. Methods that enable estimation and enhance the accuracy are presented and their effects are evaluated. Moreover, it is empirically demonstrated that the performance of the system is comparable to the accuracy of a high-end device for 3–4 orders of magnitude less price; achieving mean absolute error of 0.12 breaths per minute in the most realistic scenario of the experiments.

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Registry

Crossref · 10.1109/ipsn.2014.6846741

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1 of 1 references verified0 citation errors · 0 not checkable

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  • High frequency and sub-millimetre wavelength radio technologies have demonstrated the ability to capture physiological signals without body contact.

    “In the past decade, high frequency and sub-millimetre wavelength radio technologies have demonstrated the ability to capture physiological signals without body contact.”
  • Through signal processing, it is possible to extract biological information, such as breathing patterns, heart rate and full-body motion, from radio signals.

    “Through signal processing, it is possible to extract biological information, such as breathing patterns, heart rate and full-body motion from these findings71,73–75.”

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Authors
Kaltiokallio, O., Yigitler, H., Jantti, R., & Patwari, N.
Affiliations
  • Aalto University (FI)
  • University of Utah (US)
Venue
IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks
Publisher
IEEE
Published
2014-04
Pages
59-69
OpenAlex
W4253962816
Cited by
101
References
1
Citations by year
2026: 1 · 2025: 3 · 2024: 12 · 2023: 10 · 2022: 6 · 2021: 9 · 2020: 8 · 2019: 13 · 2018: 15 · 2017: 9 · 2016: 9 · 2015: 5 · 2014: 1
FWCI
15.54
Type
conference paper
Language
en
Open access
closed
Locations
ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) (publishedVersion)
Funders
National Science Foundation (1035565, 0855261)
Topics
  • Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
  • Physical Sciences › Engineering › Biomedical Engineering › Wireless Body Area Networks
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › ECG Monitoring and Analysis
Keywords
respiratory rate estimation, received signal strength, vital signs, low-cost health monitoring

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