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Estimation of respiratory rate in various environments using microphones embedded in face masks.
Lim, Chhayly; Kim, Jungyeon; Kim, Jeongseok; Kang, Byeong-Gwon; Nam, Yunyoung.
Afiliação
  • Lim C; Department of ICT Convergence, Soonchunhyang University, Asan, 31538 South Korea.
  • Kim J; ICT Convergence Research Center, Soonchunhyang University, Asan, 31538 South Korea.
  • Kim J; Department of ICT Convergence, Soonchunhyang University, Asan, 31538 South Korea.
  • Kang BG; Department of Information and Communication Engineering, Soonchunhyang University, Asan, 31538 South Korea.
  • Nam Y; Department of Computer Science and Engineering, Soonchunhyang University, Asan, 31538 South Korea.
J Supercomput ; 78(17): 19228-19245, 2022.
Article em En | MEDLINE | ID: mdl-35754514
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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Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 1_ASSA2030 Base de dados: MEDLINE Aspecto: Patient_preference Idioma: En Revista: J Supercomput Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 1_ASSA2030 Base de dados: MEDLINE Aspecto: Patient_preference Idioma: En Revista: J Supercomput Ano de publicação: 2022 Tipo de documento: Article