Intelligent Earable Systems for Equitable Healthcare

Abstract

Access to basic medical resources like hearing care is influenced by factors like an individual’s birth country. This lack of access is often due to the prohibitively high prices of medical devices which cannot be afforded by most of the world. At the same time, mobile sensors and technologies have advanced substantially over the last two decades and are now ubiquitous. In this dissertation, we develop a unique approach to societally impactful research that involves identifying problems that are important in the medical domain, and formulating solutions which are interesting from a computational standpoint. Through this process, we create a suite of intelligent earable systems for equitable healthcare that breaks the conventional wisdom that expensive medical devices are needed for high quality clinical testing. By working towards adoption in the real-world, these systems are now transforming the field of audiology and having societal impact. The key challenge in designing these systems is in leveraging low-cost, commodity hardware to perform medical diagnostics of the ear at scale while still achieving high-quality clinical performance. We design computational methods spanning applied machine learning, wireless sensing, signal processing and embedded hardware to enable these systems to generalize across different hardware and real-world environments. The first system can detect ear infections using the speakers and microphones on a smartphone and a paper cone. The second system enables low-cost newborn hearing screening using earphones and wireless earbuds. The third system is an inexpensive smartphone-based tympanometry system to make screening of middle ear disorders more accessible. Looking forward, this dissertation sets the stage for the mobile systems community which is uniquely positioned to develop wearable and mobile technologies that can alleviate global health inequity and ensure that every human on the planet has access to basic medical tools.