OBJECTIVE: The Control of Noise at Work Regulations came into force in Great Britain in 2005, requiring all work environments to be monitored for potentially harmful noise exposure levels. This study evaluated the effectiveness of a number of iPhone phone applications (apps) (Apple, Cupertino, CA) to accurately measure noise exposure, which may prove effective when a specialist-calibrated sound level meter is not readily available. METHODS: Suitable apps were identified using the search terms noise and decibel through the App Store (Apple). Apps that were free to download and had at least one rating were included. Apps were evaluated using a calibrated pure tone sound field and a soundproof testing booth. A 3-frequency audiogram (1000 Hz, 2000 Hz, and 4000 Hz) was used at 25 dB, 40 dB, 55 dB, 70 dB, and 85 dB. Linear regression was carried out to assess accuracy. RESULTS: Nine apps were tested in total, with four out of nine providing a goodness-of-fit coefficient (R2 value) over 0.9. The most effective app was found to be the NIOSH (National Institute for Occupational Safety and Health) Sound Level Meter (EA LAB, Slovenia) with an R2 of 0.97. The least effective app was the Decibel Meter With Recorder (Jianhua Ming, China) with an R2 of 0.62. CONCLUSION: This study has shown significant variation in the ability of iPhone apps (Apple) to accurately predict environmental dB levels. However, if the correct app is used, an iPhone represents a relatively reliable means of measuring noise exposure levels when a specialist calibrated sound level meter is not readily available. LEVEL OF EVIDENCE: NA Laryngoscope, 131:E59-E62, 2021.
OBJECTIVE: The Control of Noise at Work Regulations came into force in Great Britain in 2005, requiring all work environments to be monitored for potentially harmful noise exposure levels. This study evaluated the effectiveness of a number of iPhone phone applications (apps) (Apple, Cupertino, CA) to accurately measure noise exposure, which may prove effective when a specialist-calibrated sound level meter is not readily available. METHODS: Suitable apps were identified using the search terms noise and decibel through the App Store (Apple). Apps that were free to download and had at least one rating were included. Apps were evaluated using a calibrated pure tone sound field and a soundproof testing booth. A 3-frequency audiogram (1000 Hz, 2000 Hz, and 4000 Hz) was used at 25 dB, 40 dB, 55 dB, 70 dB, and 85 dB. Linear regression was carried out to assess accuracy. RESULTS: Nine apps were tested in total, with four out of nine providing a goodness-of-fit coefficient (R2 value) over 0.9. The most effective app was found to be the NIOSH (National Institute for Occupational Safety and Health) Sound Level Meter (EA LAB, Slovenia) with an R2 of 0.97. The least effective app was the Decibel Meter With Recorder (Jianhua Ming, China) with an R2 of 0.62. CONCLUSION: This study has shown significant variation in the ability of iPhone apps (Apple) to accurately predict environmental dB levels. However, if the correct app is used, an iPhone represents a relatively reliable means of measuring noise exposure levels when a specialist calibrated sound level meter is not readily available. LEVEL OF EVIDENCE: NA Laryngoscope, 131:E59-E62, 2021.