Big Data Analytics in Healthcare: Design and Implementation for a Hearing Aid Case Study

Modern hearing aids (HAs) are not simple passive sound enhancers, but rather complex devices that can log (via smart-phones) multivariate real-time data from the acoustic environment of a user. In the EVOTION project (www.h2020evotion.eu) such hearing aids are integrated with a Big Data analytics (BDA) platform to bring about ecologically valid evidence for policy-making within the hearing healthcare sector. Here, we present the background of the BDA platform and a concrete case study of how longitudinally sampled data from HAs can 1) support hypotheses about HA usage prognosis, and 2) bring new knowledge of how HAs are used across a typical day. In five participants, we found that the hourly HA usage was negatively associated with both the mean and the variance of the signal-to-noise ratio, and that increases in the daily total HA usage were associated with higher and more diverse sound levels.

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