Explored the viability of capturing internal body sounds with a wearable device for medical applications. This project involved the construction of wearable device (with specialised acoustic circuitry) which was used to collect a dataset; the experimental procedure was designed to evaluate performance during challenging user activities and acoustic conditions. Algorithms for continuous heart monitoring and asthma symptom detection are described and evaluated. It was shown that the algorithms could be run in real-time on plausible wearable hardware. Supervised by Professor Cecilia Mascolo. Awarded “Highly Commended” dissertation prize by the University. Currently under review for publication.

Conceptually similar to the lost device tracking features included by Apple in iOS 13 (2019). The dissertation describes a novel technique for Bluetooth 5 that enables device tracking without leaking the owner's identity to untrusted observers. Supervised by Dr Robert Harle. Some results from dissertation included in a paper at PerCom 2018.