Date/Time
Date(s) - 06/09/2016
10:00 am - 11:00 am
Location
Social, Genetic and Developmental Psychiatry Centre (MRC), Seminar Room A & B
Category(ies)
Title: From Mobile Phone based Monitoring of Depressive States to Data-Driven Behaviour Interventions
Abstract: Existing interview-based studies in the literature have shown that depression leads to a reduction of mobility and activity levels. We believe that the support provided by new mobile technologies can help to tackle this problem providing new ways for supporting both patients and healthcare officers, possibly through the automatic delivery of behaviour interventions. In this talk I will discuss the current activities of my lab in this area.
In particular, I will show how mobile phones can be used to collect and analyse mobility patterns of individuals in order to quantitatively understand how mental health problems affect their daily routines and behaviour and how potential changes can be automatically detected. I will demonstrate that it is possible to observe a non-trivial correlation between mobility patterns and depressive mood using data collected by means of smartphones. I will also discuss our on-going efforts in designing inference algorithms as a basis for unobtrusive monitoring and prediction of depressive mood disorders.
Bio: Mirco Musolesi is a Reader in Data Science at the Department of Geography at University College London and a Faculty Fellow at the Alan Turing Institute. He received a PhD in Computer Science from University College London and a Master in Electronic Engineering from the University of Bologna. He held research and teaching positions at Dartmouth College, Cambridge, St Andrews and Birmingham. He is a computer scientist with a strong interest in sensing, modelling, understanding and predicting human behaviour and dynamics in space and time, at different scales, using the “digital traces” we generate daily in our online and offline lives. He is interested in developing mathematical and computational models as well as implementing real-world systems based on them. This work has applications in a variety of domains, such as intelligent systems design, digital health, security and privacy, and ubiquitous computing. More details about his research profile can be found at: http://www.ucl.ac.uk/~ucfamus/