Remote monitoring of patient respiration with mask attachment—a pragmatic solution for medical facilities
Remote monitoring of vital signs in infectious patients minimizes the risks of viral transmissions to healthcare professionals. Evidence indicates that donning face masks reduces the risk of viral transmissions and is now the norm in medical facilities. We propose attaching an acoustic-sensing de...
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sg-ntu-dr.10356-1549562022-05-27T01:16:14Z Remote monitoring of patient respiration with mask attachment—a pragmatic solution for medical facilities Koh, Vivian Ci Ai Ang, Yi Yang Ser, Wee Tan, Rex Xiao School of Electrical and Electronic Engineering Aevice Health Pte Ltd Engineering::Electrical and electronic engineering Acoustic Sensor Face Mask Remote monitoring of vital signs in infectious patients minimizes the risks of viral transmissions to healthcare professionals. Evidence indicates that donning face masks reduces the risk of viral transmissions and is now the norm in medical facilities. We propose attaching an acoustic-sensing device onto face masks to assist medical facilities in monitoring patients' respiration remotely. Usability and functionality studies of the modified face mask were evaluated on 16 healthy participants, who were blindfolded throughout the data collection. Around half of the participants noticed the difference between the modified and unmodified masks but they also reported there was no discomfort in using the modified mask. Respiratory rates of the participants were evaluated for one minute and the mean error of respiratory rate was found to be 2.0 +/- 1.3 breath per minute. As all participants were healthy, the wheeze detection algorithm was assessed by playing 176 wheezes and 176 normal breaths through a foam mannequin. The recordings were played at three different times to account for varying environmental noise. The overall accuracy of the wheeze detection algorithm was 91.9%. The current findings support and suggest the use of the mask attachment in medical facilities. Published version This research is funded by Aevice Health Pte Ltd., a medical device research and development company based in Singapore. 2022-05-27T01:16:14Z 2022-05-27T01:16:14Z 2021 Journal Article Koh, V. C. A., Ang, Y. Y., Ser, W. & Tan, R. X. (2021). Remote monitoring of patient respiration with mask attachment—a pragmatic solution for medical facilities. Inventions, 6(4), 81-. https://dx.doi.org/10.3390/inventions6040081 2411-5134 https://hdl.handle.net/10356/154956 10.3390/inventions6040081 2-s2.0-85119128576 4 6 81 en Inventions © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). application/pdf |
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Engineering::Electrical and electronic engineering Acoustic Sensor Face Mask Koh, Vivian Ci Ai Ang, Yi Yang Ser, Wee Tan, Rex Xiao Remote monitoring of patient respiration with mask attachment—a pragmatic solution for medical facilities |
description |
Remote monitoring of vital signs in infectious patients minimizes the risks
of viral transmissions to healthcare professionals. Evidence indicates that
donning face masks reduces the risk of viral transmissions and is now the norm
in medical facilities. We propose attaching an acoustic-sensing device onto
face masks to assist medical facilities in monitoring patients' respiration
remotely. Usability and functionality studies of the modified face mask were
evaluated on 16 healthy participants, who were blindfolded throughout the data
collection. Around half of the participants noticed the difference between the
modified and unmodified masks but they also reported there was no discomfort in
using the modified mask. Respiratory rates of the participants were evaluated
for one minute and the mean error of respiratory rate was found to be 2.0 +/-
1.3 breath per minute. As all participants were healthy, the wheeze detection
algorithm was assessed by playing 176 wheezes and 176 normal breaths through a
foam mannequin. The recordings were played at three different times to account
for varying environmental noise. The overall accuracy of the wheeze detection
algorithm was 91.9%. The current findings support and suggest the use of the
mask attachment in medical facilities. |
author2 |
School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Koh, Vivian Ci Ai Ang, Yi Yang Ser, Wee Tan, Rex Xiao |
format |
Article |
author |
Koh, Vivian Ci Ai Ang, Yi Yang Ser, Wee Tan, Rex Xiao |
author_sort |
Koh, Vivian Ci Ai |
title |
Remote monitoring of patient respiration with mask attachment—a pragmatic solution for medical facilities |
title_short |
Remote monitoring of patient respiration with mask attachment—a pragmatic solution for medical facilities |
title_full |
Remote monitoring of patient respiration with mask attachment—a pragmatic solution for medical facilities |
title_fullStr |
Remote monitoring of patient respiration with mask attachment—a pragmatic solution for medical facilities |
title_full_unstemmed |
Remote monitoring of patient respiration with mask attachment—a pragmatic solution for medical facilities |
title_sort |
remote monitoring of patient respiration with mask attachment—a pragmatic solution for medical facilities |
publishDate |
2022 |
url |
https://hdl.handle.net/10356/154956 |
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1734310333604954112 |