We are building SoundProof, a mobile phone tool to capture a record of noise levels a person is exposed to throughout the day. Mobile phones equipped with audio recording capabilities and GPS interfaces can automatically and objectively collect sound data otherwise unavailable to noise researchers. Researchers at the University of Southern California's Keck School of Medicine will use these high resolution data to evaluate relationships between a subject's location, their noise exposure, and their activity to investigate associations between noise and health indicators such as perceived stress, blood pressure, or longer-term health outcomes such as asthma in children or hypertension in adults.

Background

Environmental noise is an underappreciated environmental hazard, and has been linked to several important stress-related health outcomes including hypertension, heart disease, stroke, and heart attack. However, nearly all of these health studies have been conducted using only estimates of noise exposure from either outdoor measurements, computer modeling, or self-reporting. None of these are particularly accurate means of estimating true noise exposure, especially since most peoples. time is spent indoors where significant but widely-varying noise attenuation occurs.

Now there is potential to make true noise exposure measurements with large numbers of subjects using mobile phone technology, and which will advance the study of the health effects of noise exposure to a new level. Mobile phones have become nearly ubiquitous, lightweight and fairly cheap, providing a potential platform from which to obtain real-time, true noise exposure from large numbers of people cheaply and efficiently. Existing microphones can be readily adapted to measure the most frequent sound metric, the frequency-adjusted (A-weighted) equivalent sound level Leq (A), the gold standard in measurement studies. Combined with GPS technology, also readily available on mobile phones, different noise environments can be segregated by time and location for further exposure refinement.

We will compare sound level data collected with the mobile phone and a professional sound level meter in three stages. After each stage, if necessary, modifications will be made until mobile phone data meets our accuracy requirements.

The first stage was in lab, where we collected data from the mobile phone and professional sound meter in response to controlled stimulus. Results from this stage indicate that the phone can be used to compute reliable A-level data, as compared to the professional sound meter.

This plot is of A-weighted sound pressure levels computed on the phone (blue and green line) and recorded using the BK-Meter (remaining flat lines). The blue line shows the uncalibrated levels collected on the phone. Once the data from the phone is calibrated (green line), the reported levels match up exactly to those reported by the BK-meter. This plot demonstrates that the phone can be used to feasibly report accurate A-weighting sound pressure levels. Future work is to repeat this experiment outdoors, and compare results, using this calibration.

In the second stage, we will have a user carry the mobile phone throughout the day, along with the professional sound meter. In these outdoor studies, we will aim to measure noise in different environments, which will have characteristics, such as frequency and dynamic range. For example, we will ensure to include traffic noise, both in and out of a vehicle; a crowded room of people such as a restaurant; a classroom with a single speaker; loud television; wind; an area of relative quiet (both indoors and out); and any other location where people spend a significant amount of their time.

Funds and support from Switzer Foundataion, and Green Empowerment.

We are working with Dr. Scott Fruin to use soundproof to monitor individual's exposure to environmental noise in urban areas.