A Scalable Data Pipeline to Assess the Physiological Effects of Audio-Based Interventions

Abstract

Traditionally, the impact of audio therapy on individuals has been examined by qualitative means, asking people to self-reflect on their listening behaviour and sense of well-being. The objective of the thesis was to create a framework to complement subjective measurements with wide margins of error with more quantitative instruments. Quantitative analysis was employed to identify patterns and correlations within the collected data. The process involved defining measurement parameters, developing a prototype for data collection, and evaluating the framework’s effectiveness through user testing and feedback analysis. The study shows that complementing subjective feedback with measurable listening metric provides more comprehensive results on the impact of audio therapy. The framework created in this study allows for a scalable and evidence-based approach to evaluating audio-based interventions, offering practical benefit for research and commercial applications in the wellness sector.