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Appl Acoust. 2015 Jan 15;102:1-11.

Pilot study of methods and equipment for in-home noise level measurements.

Author information

1
Department of Environmental Health Sciences and Risk Science Center, University of Michigan, 1420 Washington Heights, SPH I 6611 Ann Arbor, MI 48109.
2
Westat, 1600 Research Blvd, Rockville, MD 20850.
3
Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD 20852.

Abstract

Knowledge of the auditory and non-auditory effects of noise has increased dramatically over the past decade, but indoor noise exposure measurement methods have not advanced appreciably, despite the introduction of applicable new technologies. This study evaluated various conventional and smart devices for exposure assessment in the National Children's Study. Three devices were tested: a sound level meter (SLM), a dosimeter, and a smart device with a noise measurement application installed. Instrument performance was evaluated in a series of semi-controlled tests in office environments over 96-hour periods, followed by measurements made continuously in two rooms (a child's bedroom and a most used room) in nine participating homes over a 7-day period with subsequent computation of a range of noise metrics. The SLMs and dosimeters yielded similar A-weighted average noise levels. Levels measured by the smart devices often differed substantially (showing both positive and negative bias, depending on the metric) from those measured via SLM and dosimeter, and demonstrated attenuation in some frequency bands in spectral analysis compared to SLM results. Virtually all measurements exceeded the Environmental Protection Agency's 45 dBA day-night limit for indoor residential exposures. The measurement protocol developed here can be employed in homes, demonstrates the possibility of measuring long-term noise exposures in homes with technologies beyond traditional SLMs, and highlights potential pitfalls associated with measurements made by smart devices.

KEYWORDS:

National Children's Study; exposure assessment; mHealth; mobile app; noise; smartphone; sound level

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