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Estimation of respiratory rate in various environments using microphones embedded in face masks

Authors
Lim, ChhaylyKim, JungyeonKim, JeongseokKang, Byeong-GwonNam, Yunyoung
Issue Date
Nov-2022
Publisher
Kluwer Academic Publishers
Keywords
Respiratory rate; Power spectral density; Microphone; Face mask; Wearable health device
Citation
Journal of Supercomputing, v.78, no.17, pp 19228 - 19245
Pages
18
Journal Title
Journal of Supercomputing
Volume
78
Number
17
Start Page
19228
End Page
19245
URI
https://scholarworks.bwise.kr/sch/handle/2021.sw.sch/21683
DOI
10.1007/s11227-022-04622-0
ISSN
0920-8542
1573-0484
Abstract
Wearable health devices and respiratory rates (RRs) have drawn attention to the healthcare domain as it helps healthcare workers monitor patients' health status continuously and in a non-invasive manner. However, to monitor health status outside healthcare professional settings, the reliability of this wearable device needs to be evaluated in complex environments (i.e., public street and transportation). Therefore, this study proposes a method to estimate RR from breathing sounds recorded by a microphone placed inside three types of masks: surgical, a respirator mask (Korean Filter 94), and reusable masks. The Welch periodogram method was used to estimate the power spectral density of the breathing signals to measure the RR. We evaluated the proposed method by collecting data from 10 healthy participants in four different environments: indoor (office) and outdoor (public street, public bus, and subway). The results obtained errors as low as 0% for accuracy and repeatability in most cases. This research demonstrated that the acoustic-based method could be employed as a wearable device to monitor RR continuously, even outside the hospital environment.
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