Together with Quantified Self Institute we did a breakout on QS research. Thomas Blomseth Christiansen and I organized a workshop/breakout session on Tracking Subjective Experience. I organized another breakout session about food tracking, which included a group of people with type 1 diabetes. And finally I did a show and tell talk about longitudinal tracking of sleep and resting heart rate.
Moreover I had the opportunity to attend the keynote by Arthur Stone on “Challenges remaining for the field of real-time data capture”, including his shout out to the “Quantified Self Movement”, as he phrased it. During the Q&A I asked him to elaborate on the role of QS from his perspective, to which he responded: I think it’s really interesting that people are becoming so interested in monitoring themselves and get feedback about themselves. To me it seems like again maybe we should think about what they are doing and what they are saying and talk to them. And perhaps talk about the hypothesis generation, because I don’t see them doing the kind of stricter scientific research that we need to do in order to confirm the associations. But I think, I mean it’s great that people are doing this and are interested in this. It’s a little worrisome that the big corporations are getting into this – I mean maybe it’s worrisome, maybe it’s great. I’m not sure. Something is happening now and I don’t know quite how this is all going to turn out.
We had the QS Copenhagen Meetup #15 with talks on continuous glucose tracking, tracking of running to achieve negative split, sleep and resting heart rate tracking, and a discussion about designing a N=1 experiment.
This year the workshop was framed as the “Disasters in Personal Informatics: The Unpublished Stories of Failure and Lessons Learned”. The idea was to stimulate a discussion on the challenges involved in conducting research in personal informatics. Nine interesting papers were discussed in three themes as part of the workshop program: Personal Informatics in Life, Data Collection and Quality, and Engagement in Longitudinal Studies.
My PhD student Andrea Cuttone and I presented our work: “The Long Tail Issue in Large Scale Deployment of Personal Informatics” discussing issues in carrying out Personal Informatics research as part of our large-scale SensibleDTU study.
With smartphones and new wearable devices it is possible to measure many different aspects of our lives, including exercising, sleep and mood. But the question is if this technology can change our habits?
Our team from DTU Compute uses Science in the City as the foundation for a scientific study – and we use the official SciCity app to do this. We have included a step counter feature in the app and use the app to study the factors that motivate to take more steps. Our study is based on the two exciting scientific fields: Quantified Self and Network Science.
Quantified Self addressing how self-monitoring (for instance apps on smartphones or wearable gadgets) influence our self-perception and Network Science studying the mathematics that describes structure and dynamics in our social networks. Via family, friends, and colleagues, we’re connected to a global social network. In many ways, our social networks show who we are. And our research shows that this information reveals which fundamental values and interests characterize us. We use information about the connections on, e.g. Facebook to explore which factors motivate the user to take more steps.
I appeared on the TV2 “Go’ aften Danmark” show tonight (May 12) to discuss the phenomenon quantified self (in Danish: selvmåling) and also the potential for our future health care system. The hosts were really good sports, as they had themselves been self-tracking steps, weight, body fat, activity, and mood for about a week.
The show is available on the TV2 Play website (subscription required) starting out with a general discussion of quantified self and self-tracking and in the end of the show we discuss the future potential of self-tracking.
This weekend (May 9-11) I attended the Quantified Self Europe Conference 2014 in Amsterdam. Yet again a very packed conference program with lot’s of interesting presentations, show&tell, breakout sessions, and as usual 10 different things going on at the same time.
I presented our poster on Visualizing QS Data Using Time Spirals (PDF), which got a lot of attention from the conference participants. The poster was co-authored with my PhD student Andrea Cuttone, and collegue Associate Professor Sune Lehmann.
In addition I led a breakout session on “Strategies for Managing Personal Data”, which led into an interesting discussion of strategies, tools, and the common struggle experienced by multiple participants that personal data management is still a largely complex process.
Interestingly the conversation recently have moved more towards discussing the potential of self-tracking in healthcare. And sure enough the conversation during the Q&A session was primarily focused on the potential and the consequences for the healthcare system (and patient) in the future. Some addressed this as a question of power and who has the upper hand (doctors and the system losing power), but I believe it’s not productive for the conversation to see it that way. Of course the stakeholders will eventually need to change their roles, but improved tools will be beneficial for all stakeholders. The conversation continues…
This week I’m attending the Quantified Self Global Conference 2013 in San Francisco.
Quantified Self, Personal Informatics, and Life Logging has gained increased attention among scientists and researchers. So at the conference I will be leading a breakout session on QS Research, where we will discuss challenges, opportunities, and future directions in this research domain.
Over the last couple of years self-tracking has gained increased interest with the availability of smartphones and low-cost wearable sensors. The increasing quantities of data that we can capture about human behavior and interactions are key to future improvements in health and well-being.
In the paper we propose an interactive visualization technique QS Spiral that aims to capture the periodic properties of quantified self data and let the user explore those recurring patterns. The approach is based on time-series data visualized as a spiral structure. The interactivity includes the possibility of varying the time span and the time frame shown, allowing for different levels of detail and the discoverability of repetitive patterns in the data on multiple scales.