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

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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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Data availability

The datasets generated and/or analyzed during the current study are not publicly available due to privacy and confidentiality agreements as well as other restrictions, but are available from the corresponding author on reasonable request.

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Acknowledgements

This research was supported by Korea Institute for Advancement of Technology(KIAT) grant funded by the Korea Government(MOTIE) (P0012724, The Competency Development Program for Industry Specialist) and the Soonchunhyang University Research Fund.

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Authors and Affiliations

  1. Department of ICT Convergence, Soonchunhyang University, Asan, 31538, South Korea

    Chhayly Lim & Jeongseok Kim

  2. ICT Convergence Research Center, Soonchunhyang University, Asan, 31538, South Korea

    Jungyeon Kim

  3. Department of Information and Communication Engineering, Soonchunhyang University, Asan, 31538, South Korea

    Byeong-Gwon Kang

  4. Department of Computer Science and Engineering, Soonchunhyang University, Asan, 31538, South Korea

    Yunyoung Nam

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  1. Chhayly Lim
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Correspondence to Yunyoung Nam.

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Lim, C., Kim, J., Kim, J. et al. Estimation of respiratory rate in various environments using microphones embedded in face masks. J Supercomput 78, 19228–19245 (2022). https://doi.org/10.1007/s11227-022-04622-0

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