Estimation of respiratory rate in various environments using microphones embedded in face masks
- Authors
- Lim, Chhayly; Kim, Jungyeon; Kim, Jeongseok; Kang, Byeong-Gwon; Nam, 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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Collections - College of Engineering > Department of Computer Science and Engineering > 1. Journal Articles
- College of Engineering > Department of Information and Communication Engineering > 1. Journal Articles
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