Event: From Mobile Phone based Monitoring of Depressive States to Data-Driven Behaviour Interventions

Date: Tuesday 6th September, 2016

Time: 10:00am - 11:00am

Location: Rooms A&B, MRC Social, Genetic & Developmental Psychiatry (SGDP) Centre, Institute of Psychiatry, Psychology and Neuroscience, De Crespigny Park, 16 Denmark Hill, London, SE5 8AF 

Existing interview-based studies in the literature have shown that depression leads to reduced mobility and activity levels. Some researchers 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,  Mirco Musolesi (University College London, Alan Turing Institute) will discuss the current activities of his lab in this area.

In particular, he will discuss 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. He 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, and will also discuss ongoing efforts to design inference algorithms as a basis for unobtrusive monitoring and prediction of depressive mood disorders.

The Seminar will take place at 10am on Tuesday 6th September, and is open to all.

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 Masters degree in Electronic Engineering from the University of Bologna. He has 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. 

 


Tags: Events - Bioinformatics & statistics - Precision psychiatry -

By NIHR Maudsley BRC at 31 Aug 2016, 12:11 PM


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