Abstract
Part of the IET EngTalk and BCS Lecture Series.
What can data from devices we carry with us in our daily activities really reveal about our health and wellbeing?
Considerable research has been conducted into mobile and wearable systems for human health monitoring. This concentrates on either devising sensing and systems techniques to effectively and efficiently collect data about users, and patients or in studying mechanisms to analyse the data coming from these systems accurately. In both cases, these efforts raise important technical as well as ethical issues.
In this talk, I plan to reflect on the challenges and opportunities that mobile and wearable health systems are introducing for the community, the developers as well as the users. I will use examples from my group's ongoing research on exploring machine learning and data analysis for health application in collaboration with epidemiologists and clinicians.
In particular, I will discuss our project on using audio signals for disease diagnostics and our recent work in the context of COVID-19: a crowdsourced collected through mobile apps (covid-19-sounds.org) of respiratory sounds (coughs, breathing and voice) to pre-screen and diagnose COVID-19.
