Literature DB >> 27794313

Evaluation of smartphone sound measurement applications (apps) using external microphones-A follow-up study.

Chucri A Kardous1, Peter B Shaw1.   

Abstract

This follow-up study examines the accuracy of selected smartphone sound measurement applications (apps) using external calibrated microphones. The initial study examined 192 apps on the iOS and Android platforms and found four iOS apps with mean differences of ±2 dB of a reference sound level measurement system. This study evaluated the same four apps using external microphones. The results showed measurements within ±1 dB of the reference. This study suggests that using external calibrated microphones greatly improves the overall accuracy and precision of smartphone sound measurements, and removes much of the variability and limitations associated with the built-in smartphone microphones.

Entities:  

Year:  2016        PMID: 27794313      PMCID: PMC5102154          DOI: 10.1121/1.4964639

Source DB:  PubMed          Journal:  J Acoust Soc Am        ISSN: 0001-4966            Impact factor:   1.840


  2 in total

1.  Improving the accuracy of smart devices to measure noise exposure.

Authors:  Benjamin Roberts; Chucri Kardous; Richard Neitzel
Journal:  J Occup Environ Hyg       Date:  2016-11       Impact factor: 2.155

2.  Evaluation of smartphone sound measurement applications.

Authors:  Chucri A Kardous; Peter B Shaw
Journal:  J Acoust Soc Am       Date:  2014-04       Impact factor: 1.840

  2 in total
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Journal:  J Occup Environ Hyg       Date:  2018-05       Impact factor: 2.155

2.  Use of an Application to Verify Classroom Acoustic Recommendations for Children Who Are Hard of Hearing in a General Education Setting.

Authors:  Meredith Spratford; Elizabeth A Walker; Ryan W McCreery
Journal:  Am J Audiol       Date:  2019-11-04       Impact factor: 1.493

3.  The potential use of a NIOSH sound level meter smart device application in mining operations.

Authors:  Kan Sun; Chucri A Kardous; Peter B Shaw; Brian Kim; Jessie Mechling; Amanda S Azman
Journal:  Noise Control Eng J       Date:  2019-01-01       Impact factor: 0.527

4.  GRC-Sensing: An Architecture to Measure Acoustic Pollution Based on Crowdsensing.

Authors:  Willian Zamora; Elsa Vera; Carlos T Calafate; Juan-Carlos Cano; Pietro Manzoni
Journal:  Sensors (Basel)       Date:  2018-08-08       Impact factor: 3.576

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Authors:  Douglas Leaffer; Christopher Wolfe; Steve Doroff; David Gute; Grace Wang; Patrick Ryan
Journal:  Int J Environ Res Public Health       Date:  2019-01-23       Impact factor: 3.390

6.  Towards the Interpretation of Sound Measurements from Smartphones Collected with Mobile Crowdsensing in the Healthcare Domain: An Experiment with Android Devices.

Authors:  Robin Kraft; Manfred Reichert; Rüdiger Pryss
Journal:  Sensors (Basel)       Date:  2021-12-28       Impact factor: 3.576

7.  Indoor noise level measurements and subjective comfort: Feasibility of smartphone-based participatory experiments.

Authors:  Carlo Andrea Rozzi; Francesco Frigerio; Luca Balletti; Silvia Mattoni; Daniele Grasso; Jacopo Fogola
Journal:  PLoS One       Date:  2022-01-27       Impact factor: 3.240

8.  Are Smartwatches a Suitable Tool to Monitor Noise Exposure for Public Health Awareness and Otoprotection?

Authors:  Tim Fischer; Stephan Schraivogel; Marco Caversaccio; Wilhelm Wimmer
Journal:  Front Neurol       Date:  2022-03-23       Impact factor: 4.003

9.  Accurate Ambient Noise Assessment Using Smartphones.

Authors:  Willian Zamora; Carlos T Calafate; Juan-Carlos Cano; Pietro Manzoni
Journal:  Sensors (Basel)       Date:  2017-04-21       Impact factor: 3.576

  9 in total

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