Computer Laboratory

Mobile and Sensing Health

This page describes the group's effort in mobile health monitoring through mobile and wearable technologies. Through various sources of funding through the years we have made various efforts to support health monitoring with mobile and sensing. This page summarizes our efforts in this sense.

Project SAMOA: Early Alzheimer's Diagnostics

This project is about the use of technology to support the diagnostics of Alzheimer's disease stages. It was seed funded by the Alan Turing Institute as well as by the MRC Confidence in Concept call. We are at the early stages of this project.

Project Emotion Sense

This project started with the development of a framework to detect emotions from speach as collected through a mobile phone microphone. This was funded by EPSRC CambridgeSens. More information on the project and its Nokia implementation can be found here.

Publication

  • EmotionSense: A Mobile Phones based Adaptive Platform for Experimental Social Psychology Research Kiran K. Rachuri, Mirco Musolesi, Cecilia Mascolo, Peter J. Rentfrow, Chris Longworth, Andrius Aucinas. In Proceedings of the 12th ACM International Conference on Ubiquitous Computing (UbiComp 2010). Copenhagen, Denmark. September 2010. PDF
  • Energy-Accuracy Trade-offs in Querying Sensor Data for Continuous Sensing Mobile Systems Kiran K. Rachuri, Mirco Musolesi, Cecilia Mascolo In Proceedings of the Mobile Context-Awareness: Capabilities, Challenges and Applications Workshop (Colocated with UbiComp 2010). Copenhagen, Denmark. September 2010.PDF
  • Smart Phone based Systems for Social Psychological Research: Challenges and Design Guidelines Kiran K. Rachuri, Cecilia Mascolo In Proceedings of the 3rd Annual ACM S3 Workshop (S3 2011, Colocated with MobiCom 2011). Las Vegas, USA. September 2011.PDF

The project then received futher funding through EPSRC Project UBHAVE. We advanced our research by releasing an our opensource library for development of mobile sensing applications for Android here. On top of this library various applications have been developed. In the context of project Emotion Sense we released an Android application for mood monitoring that uses sensing and mood reports from the user (but not the microphone and not the automatic emotion recognition framework described above). We have collected over three years of data with this software which is being analyzed for research.

Publication

  • Mobile sensing at the service of mental well-being: a large-scale longitudinal study. Sandra Servia-Rodríguez, Kiran K. Rachuri, Cecilia Mascolo, Peter J. Rentfrow, Neal Lathia, Gillian M. Sandstrom. In Proceedings of 26th International World Wide Web Conference (WWW 2017). Computational Health Track. Perth, Australia. April 2017. [PDF].
  • Happier People Live More Active Lives: Using smartphones to link happiness and physical activity. Neal Lathia, Gillian M. Sandstrom, Cecilia Mascolo, Peter J. Rentfrow. In PLOS ONE. [Link to Paper. ]
  • Putting Mood in Context: Using Smartphones to Examine How People Feel in Different Locations. Gillian Sandstrom, Neal Lathia, Cecilia Mascolo, Peter J Rentfrow. Special Issue on Within-Person Variability. Journal of Research in Personality. [Link to Paper]
  • Mobile-based Experience Sampling for Behaviour Research. Veljko Pejovic, Neal Lathia, Cecilia Mascolo and Mirco Musolesi. Book chapter in Emotions and Personality in Personalized Services. Springer. 2015. PDF
  • Contextual Dissonance: Design Bias in Sensor-Based Experience Sampling Methods. Neal Lathia, Kiran Rachuri, Cecilia Mascolo, Peter J. Rentfrow. In Proceeding of ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2013). Zurich, Switzerland. September 2013. PDF.
  • Open Source Smartphone Libraries for Computational Social Science. Neal Lathia, Kiran Rachuri, Cecilia Mascolo, George Roussos. In Proceeding of ACM International Workshop on Mobile Systems for Computational Social Science (MCSS 2013). Zurich, Switzerland. September 2013. PDF
  • Smartphones for Large-scale Behaviour Change Interventions. Neal Lathia, Veljko Pejovic, Kiran Rachuri, Cecilia Mascolo, Mirco Musolesi, Peter J. Rentfrow. In IEEE Pervasive Computing. Special Issue on Understanding and Changing Behavior. PDF

People

Over the years a number of people have contributed to this project:

  • Andrius Aucinas
  • Chloe Brown
  • Neal Lathia
  • Chris Longworth
  • Cecilia Mascolo
  • Mirco Musolesi
  • Kiran Rachuri
  • Jason Rentfrow
  • Gillian Sandstorm
  • Sandra Servia-Rodriguez

Project QSense

As part of an MRC funded pilot study we developed a collaboration to help users who want to stop smoking to do so with the help of mobile technologies. Our effort is described in details here. By using the Emotion Sense mobile sensing development library for Android we have developed QSense, a mobile app which helps delivery timely interventions to users willing to quit smoking. The pilot study is ongoing.

Publication

  • The feasibility of a context sensing smoking cessation smartphone application (Q Sense): a mixed methods study. Felix Naughton, Sarah Hopewell, Neal Lathia, Rik Schalbroeck, Chloe Brown, Cecilia Mascolo, Stephen Sutton. JMIR mHealth uHealth. To Appear.

People

Over the years a number of people have contributed to this project:

  • Chloe Brown
  • Sarah Hopewell
  • Neal Lathia
  • Cecilia Mascolo
  • Felix Naughton
  • Stephen Sutton