COVID-Beat: a low-cost breath monitoring approach for people in quarantine during the pandemic

Author:

Atif Muhammad1ORCID,Muralidharan Shapna1ORCID,Ko Heedong12,Yoo Byounghyun12ORCID

Affiliation:

1. Center for Artificial Intelligence, Korea Institute of Science and Technology, 5 Hwarangro14-gil, Seongbuk-gu, Seoul 02792, South Korea

2. Artificial Intelligence and Robotics, KIST School, Korea University of Science and Technology, 5 Hwarangro14-gil, Seongbuk-gu, Seoul 02792, South Korea

Abstract

Abstract Due to COVID-19, people have to adapt to the new lifestyle until scientists develop a permanent solution for this pandemic. Monitoring the respiration rate is very important for a COVID-infected person because the Coronavirus infects the pulmonary system of the person. Two problems that arise while monitoring the breath rate are: sensors are contact based and expensive for mass deployment. A conventional wearable breath rate monitoring system burdens the COVID-affected patient and exposes the caregivers to possible transmission. A contactless low-cost breath monitoring system is required, which monitors and records the breath rate continuously. This paper proposes a breath rate monitoring system called COVID-Beat, a wireless, low-cost, and contactless Wi-Fi-based continuous breath monitoring system. This sensor is developed using off-the-shelf commonly available embedded Internet of Thing device ESP32, and the performance is validated by conducting extensive experimentation. The breath rate is estimated by extracting the channel state information of the subcarriers. The system estimates the breath rate with a maximum accuracy of 99% and a minimum accuracy of 91%, achieved by advanced subcarrier selection and fusion method. The experimental results show superior performance over the existing breath rate monitoring technologies.

Funder

Industrial Technology Innovation Program

Ministry of Trade, Industry and Energy

National Research Foundation

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computer Graphics and Computer-Aided Design,Human-Computer Interaction,Engineering (miscellaneous),Modeling and Simulation,Computational Mechanics

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. MM-FGRM: Fine-Grained Respiratory Monitoring Using MIMO Millimeter Wave Radar;IEEE Transactions on Instrumentation and Measurement;2024

2. A Low-cost ESP32-driven Wireless Key Generation System Based on Response Mechanism;2023 8th International Conference on Computer and Communication Systems (ICCCS);2023-04-21

3. Effects of Temporary Respiration Exercise with Individual Harmonic Frequency on Blood Pressure and Autonomic Balance;International Journal of Environmental Research and Public Health;2022-11-25

4. A survey on vital signs monitoring based on Wi-Fi CSI data;Computer Communications;2022-11

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