Title: Mobile Sensing at the Service of Mental Well-being: a Large-Scale Longitudinal Study

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• Sandra Servia (QMUL)
• Thursday 09 March 2017, 15:00-16:00
• FW26, Computer Laboratory, William Gates Building.

If you have a question about this talk, please contact Liang Wang.

This talk has been canceled/deleted

Measuring mental well-being with mobile sensing has been an increasingly active research topic. Pervasiveness of smartphones combined with the convenience of mobile app distribution platforms (e.g., Google Play) provide a tremendous opportunity to reach out to millions of users. However, the studies at the confluence of mental health and mobile sensing have been longitudinally limited, controlled, or confined to a small number of participants. In this talk I will report on what we believe is the largest longitudinal in-the-wild study of mood through smartphones. I will describe an Android app to collect participants’ self-reported moods and system triggered experience sampling data while passively measuring their physical activity, sociability, and mobility via their device’s sensors. I will report the results of a large-scale analysis of the data collected for about three years from ~18,000 users.

This is a rehearsal talk for WWW ’17.

Bio: Sandra Servia is a Postdoctoral Research Assistant at Queen Mary University (QMUL), where she works on privacy-preserving data analytics as part of the Databox project. Before joining QMUL , she held Research Associate positions in the Systems Research Group (SRG) of the University of Cambridge and at the HP Labs (Bristol). She completed her Ph.D. in Telematics Engineering at the University of Vigo (Spain) in 2015. From May to September 2013 she was a visiting research student in the SRG group of the University of Cambridge, and from April to August 2014 an intern in the former Social Computing Group of the HP Labs (Palo Alto, CA). Her current research interests lie in the intersection of privacy-preserving data analytics, mobile sensing and eHealth.

This talk is part of the Computer Laboratory Systems Research Group Seminar series.

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