Detailed Information

Cited 0 time in webofscience Cited 77 time in scopus
Metadata Downloads

Estimation of Respiratory Rates Using the Built-in Microphone of a Smartphone or Headset

Authors
Nam, YunyoungReyes, Bersain A.Chon, Ki H.
Issue Date
Nov-2016
Publisher
Institute of Electrical and Electronics Engineers Inc.
Keywords
Nasal sound; respiratory rate estimation; smart-phone; sound intensity; tracheal sound
Citation
IEEE Journal of Biomedical and Health Informatics, v.20, no.6, pp 1493 - 1501
Pages
9
Journal Title
IEEE Journal of Biomedical and Health Informatics
Volume
20
Number
6
Start Page
1493
End Page
1501
URI
https://scholarworks.bwise.kr/sch/handle/2021.sw.sch/8632
DOI
10.1109/JBHI.2015.2480838
ISSN
2168-2194
2168-2208
Abstract
This paper proposes accurate respiratory rate estimation using nasal breath sound recordings from a smartphone. Specifically, the proposed method detects nasal airflow using a built-in smartphone microphone or a headset microphone placed underneath the nose. In addition, we also examined if tracheal breath sounds recorded by the built-in microphone of a smartphone placed on the paralaryngeal space can also be used to estimate different respiratory rates ranging from as low as 6 breaths/min to as high as 90 breaths/min. The true breathing rates were measured using inductance plethysmography bands placed around the chest and the abdomen of the subject. Inspiration and expiration were detected by averaging the power of nasal breath sounds. We investigated the suitability of using the smartphoneacquired breath sounds for respiratory rate estimation using two different spectral analyses of the sound envelope signals: The Welch periodogram and the autoregressive spectrum. To evaluate the performance of the proposed methods, data were collected from ten healthy subjects. For the breathing range studied (6-90 breaths/min), experimental results showed that our approach achieves an excellent performance accuracy for the nasal sound as the median errors were less than 1% for all breathing ranges. The tracheal sound, however, resulted in poor estimates of the respiratory rates using either spectralmethod. For both nasal and tracheal sounds, significant estimation outliers resulted for high breathing rates when subjects had nasal congestion, which often resulted in the doubling of the respiratory rates. Finally, we show that respiratory rates from the nasal sound can be accurately estimated even if a smartphone's microphone is as far as 30 cm away from the nose.
Files in This Item
There are no files associated with this item.
Appears in
Collections
College of Engineering > Department of Computer Science and Engineering > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Nam, Yun young photo

Nam, Yun young
College of Engineering (Department of Computer Science and Engineering)
Read more

Altmetrics

Total Views & Downloads

BROWSE