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Smartphone applications for measuring noise in the intensive care unit: A feasibility study

Lee, Pyoung Jik and Hampton, Thomas (2023) 'Smartphone applications for measuring noise in the intensive care unit: A feasibility study'. Journal of Critical Care, Vol 79, e154435.

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Abstract

Purpose
This study aims to explore the suitability of using smartphone applications with low-cost external microphones in measuring noise levels in intensive care units.

Methods
Four apps and two external microphones were tested in a laboratory by generating test signals at five noise levels. The average noise levels were measured using the apps and a professional device (i.e. a sound level meter). A field test was performed in an intensive care unit with two apps and one microphone. Noise levels were measured in terms of average and maximum noise levels according to the World Health Organisation's guidance. All the measurements in both tests were conducted after acoustic calibration using a sound calibrator.

Results
Overall, apps with low-cost external microphones produced reliable results of averaged noise levels in both the laboratory and field settings. The differences between the apps and the sound level meter were within ±2 dB. In the field test, the best combination of app and microphone showed negligible difference (< 2 dB) compared to the sound level meter in terms of the average noise level. However, the maximum noise level measured by the apps exhibited significant differences from those measured by the sound level meter, ranging from −0.9 dB to −4.7 dB.

Conclusion
Smartphone apps and low-cost external microphones can be used reliably to measure the average noise level in the intensive care unit after acoustic calibration. However, professional equipment is still necessary for accurate measurement of the maximum noise level.

Item Type: Article
Subjects: W General Medicine. Health Professions > W 82 Biomedical technology (General)
Faculty: Department: Clinical Sciences & International Health > Clinical Sciences Department
Digital Object Identifer (DOI): https://doi.org/10.1016/j.jcrc.2023.154435
Depositing User: Amy Carroll
Date Deposited: 12 Oct 2023 12:16
Last Modified: 12 Oct 2023 12:16
URI: https://archive.lstmed.ac.uk/id/eprint/23313

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