Abstract

Convergent advances in on-device computing and machine learning are creating possibilities for the ubiquitous use of wearable devices in a variety of health-related applications. Audio is an essential stream of information that can be measured via such devices. Audio sensing in naturalistic settings can provide insight into a person’s day-to-day life and hence infer meaningful patterns in their lifestyle from an acoustic perspective. Egocentric audio recordings can provide important cues about a person’s mental state and well-being (eg, stress, social interaction patterns, as well as the ambient context of a person’s surroundings). In this chapter, we provide an overview of mobile audio acquisition methods and fundamental audio processing techniques, showcasing some of the state-of-the-art methodologies in this domain. We discuss example studies that highlight the utility of audio-derived cues for a variety of applications in psychology research and practice.

Date

2023

Authors

Rajat Hebbar, Arindam Jati, Tiantian Feng, Ramon Reyes, Alexander F Danvers, Matthias R Mehl, Shrikanth S Narayanan

Journal

Mobile Sensing in Psychology: Methods and Applications

Pages

258

Publisher

Guilford Publications