This study evaluated the accuracy of using smartphone sound measurement applications with different microphones to measure occupational noise exposure. Three applications (NoiSee, SPLnFFT, SoundMeter) and three microphones (internal smartphone microphone, Dayton MM-6 external microphone, MicW i436 external microphone) were tested by exposing them to pink noise at sound levels from 60-100 dBA. Statistical analysis found a significant interaction between microphone and application selection, and that some configurations could provide accurate measurements within 2 dBA of a reference sound level meter. However, the type of microphone and application significantly affected the measurements, so further research is needed to validate smartphone noise dosimetry.

1. ANSI S1.4: Speceifications for Sound Level Meters. (1992). American National Standards
Institute.
Kardous, C. a., & Shaw, P. B. (2014). Evaluation of smartphone sound measurement
applications. The Journal of the Acoustical Society of America, 135(4), EL186–EL192.
doi:10.1121/1.4865269
Nast, D., Speer, W., & Prell, C. (2014). Sound level measurements using smartphone “apps”:
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Recommended Standard Occupational Noise Exposure, Revised Criteria. (1998). National
Institutes of Occupational Safety and Health.
This study was funded by the Rackham
Graduate Student Research Grant.
Special thanks to Chuck Kardous and
NIOSH for technical support on this
project. Please note that this poster
does not constitute an endorsement
for any product or service.
The type of microphone and
application affects the measurement
made by the smartphone.
• >61% of mobile subscribers have
smartphones
• Smartphones have already been
used for a variety of purposes in
environmental health
• Smartphones already have
microphones
• Previous work has found that using
the internal iPhone microphone may
produce accurate measurements
• No studies have compared the
measurements made by the internal
microphone to cheap external
microphones.
• Measurements made with the
internal microphone are not
accurate
• Once calibrated, the external
microphones can provide very
accurate measurements
• There was a significant
interaction between the
microphone and application
selection
• There is evidence that these
devices can be used in some
circumstances to make accurate
measurements
• Further research needs to be
done to directly compare
smartphone dosimetry to
traditional noise dosimeters
Hypothesis
Background Methods
Results
Results Continued
• Three configurations were found to have the
distribution of their differences within 2 dBA of the
SLM (Figure 2)
• Of these three configurations, two were found to
have a consistent bias (Figure 3)
• There was a significant difference (p<0.05) between
different combinations of applications and
microphones (Table 1)
• There was a significant interaction between the
microphone and application (Table 1)
• The applications have very different features and user
interfaces (Table 2 & Figure 4)
Acknowledgements
Conclusions
N= 1,458; N= 162 for each configuration
Materials
• Applications chosen based on analysis done by Kardous & Shaw
2014 NoiSee ($0.99), SPLnFFT($3.99), & SoundMeter ($19.99)
• Three microphones:
MicW i436 ($159.00) Dayton MM-6 ($17.22) Internal (Default)
• 5th generation iPod Touches used in a reverberant chamber
• Larson Davis 2559 Type 1 SLM used as “gold standard”
Procedure
• Microphones (MicW & Dayton) calibrated at 94 dB in each
application
• Pink noise generated from 60-100 dBA in 5 dBA increments
• Each application and microphone combination had 18
measurements at each noise level
Analysis
• Calculated the differences between smartphone and SLM
measurements, both overall and by reference noise level
• Two way ANOVA calculated using the calculated
differences as the dependent variable, microphone and
application as factor variables
• Application features were compared
Goal
Assess the ability of commercially
available smartphone applications to
measure continuous noise exposure
using different microphones.
References
Using Commercially Available Smartphones to Measure Occupational Noise Exposure
Benjamin Roberts 1, MPH, Rick Neitzel 1, Ph.D., CIH
1 University of Michigan Department of Environmental Health Sciences;
Table 2. A summary of features for each of the tested applications.
Weightings Dosimeter Criterion Data Logging Export Data Log Interval Plot
Octave
Band
Impulse
Noise
Calibration GPS
NoiSee Flat, A,C Yes OSHA/ISO No None None No Yes No Yes No
SPLnFFT Flat, A,B,C Yes
OSHA/NIOSH/C
ustom Very limited .csv, * Unclear Yes Yes No Yes Yes
SoundMeter Flat, A,C Yes*
OSHA/NIOSH/C
ustom Yes* .csv, .mat, .txt, Customizable Yes Yes* Yes Yes Yes
*Available via in-app purchase
Table 1. Two-way ANOVA table for microphone and application
type.
Source
Partial
SS
df MS F P-value
Model 4320 8 540 187 <0.05
Application 68 2 34 12 <0.05
Microphone 3030 2 1515 525 <0.05
Application*Microphone 1604 4 401 139 <0.05
Residual 4050 1404 3
Total 8370 1412 6
Figure 1. An example of the devices running the
SoundMeter application with the three microphones.
Figure 3. Distribution of the difference between the smartphone measurement
and the SLM measurement for three different configurations stratified by the
reference noise level. N=18 for each box. The red lines represent +/- 2 dBA
which is the standard used for a type 2 SLM.
Figure 2. Distribution of the difference between the smartphone measurement
and the SLM measurement stratified by application and microphone type.
N=162 for each box. The red lines represent +/- 2 dBA which is the standard
used for a type 2 SLM.
Figure 4. Examples of the user interface for the three applications. Top Left:
SoundMeter, Top Right: NoiSee, Bottom Left: SPLnFFT.