An Exploratory Study Investigating the Accuracy of Sound Measurements in iOS Devices for Accessibility Applications

Research

Objectives: To investigate the accuracy and consistency of sound across mobile iOS devices and models to compare the measurements and adjust algorithms for collecting accessibility information in applications.

Design: Device Reliability Assessment. Setting: Measurements were collected in a research center devoid of environmental sound. Participants: Five researchers recorded sound measurements for twelve devices and two sound meters. Interventions: Two sound meters were placed parallel on the floor 6 in. apart with a Bluetooth speaker suspended 18 in. above them. Sound was played downward through the speaker that used a tone generating app. This app allowed researchers to initiate sound and manipulate frequency and volume strength. When sound was played, data was collected at ten different frequencies with each frequency having ten volume measurements recorded. For example, sound at 50Hz would be recorded at 10% volume, 20% volume, etc. Once all the measurements had been taken, the sound meters were replaced with iOS devices. The same methods for data collection were used for the iOS devices and microphones on the front of devices were utilized for sound measurements. Main Outcome Measures: Average dBs reported over five seconds across different frequencies and volumes per iOS device.

Results: Three-thousand measurements were collected, and the results demonstrated variation between the sound measurements of the iOS devices. Devices could be grouped into two categories based on the configuration of the microphones used in the devices, which differed in location, number and position. In addition, the data collected from the iOS devices differed from the sound meters used.

Conclusions: This study provided data that can be used to revise the algorithm implemented in the AccessSound application. The increased consistency among devices will ensure that collected sound measurements are accurate and will interpret the auditory accessibility of that environment with more precision. Furthermore, any rehabilitation app developers using the sensors in iOS mobile devices are made aware of the current variability among sound measurements collected by different device models and version.