Follow the Data

A data driven blog

Archive for the tag “mobile”

Health Hack Day ’12: Day 1 impressions

So as mentioned in the previous post, Health Hack Day ’12 in Stockholm is underway right now; it started with a number of lectures and a party yesterday and the actual hacking will start today, with the winning apps to be presented tomorrow. You can follow the #hhd12 hashtag on Twitter or go to the link above to see the recorded lectures.

I thought the arrangements and speaker line-up yesterday were surprisingly good, which bodes well for the survival of the Health Hack Day concept, in fact I’m sure they will be back next year. The lectures (which were recorded and can be viewed online at the link above) were given in a smallish space (part of a fin de siècle apartment complex now used as an office hotel for creative types, located near Stureplan in central Stockholm) decorated with thousands of yellow strips of paper hanging down from the ceiling – a nice-looking installation which also provided some relief from the heat in the room when the wind occasionally blew in through the window and turned the paper strips into a giant ceiling fan. Meanwhile, visitors could sip some excellent free coffee (from Stockholm roast).

Hoa Ly is a young, enterprising fellow who works for Psykologifabriken (“The Psychology Factory”) and his own sister company Hoa’s Tool Shop (both of these companies were involved in arranging the event), as well as doing clinical psychology research at Linköping university and being a successful DJ. He talked about behavior change through digital tools, exemplifying with the Viary mobile & web app which has been used successfully for depression treatment but, as I understand it, is quite general in nature so you could track any kind of behavior & goals (incidentally, the statistics interface looks a lot like the WordPress interface where I look at access statistics for this blog!) Hoa also talked about correlating data from different sources like Viary, the Zeo sleep tracker and exercise data from heiaheia.com. Integrating data from different sources is of course very interesting but I didn’t feel we quite got any really solid concrete examples here, just a general sense that it should be useful. Anyway. The most intriguing part of Hoa’s talk was when he described the launch of a new project to “disrupt the whole dance music industry” (or words to that effect). The idea is to treat DJ performances as scientific experiments and “gather data from the audience”, for instance by measuring adrenaline levels in response to song selections. Hoa and his partners have created a new  country called Yamarill (link in Swedish) to construct a narrative around which this project will be built. The inauguration of the new country will apparently be celebrated on June 1 at the Hoa’s Tool Shop office spaces. The Yamarill “delegation” has already played several DJ gigs “combining electronic dance music, technology and psychology” as they say in the linked interview (I might also add “quirky clothes”).

Pernilla Rydmark from .SE talked about different forms of crowdfunding and presented five Swedish platforms for it. .SE is also introducing an interesting form of funding called “guaranteed funding” where they pick projects that are already popular on crowdfunding platforms and promise to fund them up to their stated goal in case they don’t succeed in reaching it through the crowdfunding platform. Thus, the goal of the funding is rather paradoxically that no one should get it (because .SE is hoping that the projects will get fully funded by the crowd.)

Bill Day from Runkeeper talked about the need for an open, global health platform and presented HealthGraph, a free platform with tens or millions of users initiated by the RunKeeper team but which is expanding far beyond that community.

Mathias Karlsson from Calmark presented his company’s approach to rapid blood biomarker testing, which is making consumable platforms for colorimetric assays (the measurement of interest is transformed into a color) which can be analyzed on the spot using, for example, a smartphone camera. He brought a developer team who will attempt to build a new test (for bilirubin) into the platform in 24 hours during the hackathon part of the event.

Linus Bengtsson from FlowMinder described intriguing reality mining (or in less spectacular terms, call log analysis) work where data from mobile phone providers was used to track the movements of people during and after the Haiti earthquake, and the subsequent cholera outbreak. Linus and his team tracked 1.9 million SIM cards from Port-Au-Prince residents to obtain their estimates on migration patterns. FlowMinder is a non-profit and provides free analysis of the same kind during any kind of global disaster (in collaboration with mobile telephony providers, naturally.)

Sara Eriksson and Johan Nilsson from United Minds talked about the “new health”, including a lot of topics that have been frequently mentioned on this blog, like 23andme, PatientsLikeMe, and even the MinION sequencer from Oxford Nanopore. I had heard / thought about most of it before but what I took away from it was the concept of “biosociality” as coined by Paul Rabinow, and also that only 37% of surveyed Stockholm smart phone users did *not* want to collect data on themselves through the phone; a whopping 59% wanted not only to collect the data but to analyze it themselves.

Megan Miller from Bonnier (a Swedish media company which has an enormous influence in the media here; however Megan was working for its US branch) described Teemo, a platform for “digital wellness”, with components of collaborative adventuring and social exercise (you try to accomplish “quests” together with your friends by exercising.) Teemo looks like it has a pretty nifty design, inspired by paper cuts and Nordic (=Helsinki?) design style. As Megan put it, Teemo wants to “put fun first and track behavior in the background.)

We will see whether Follow the Data has the energy to visit again tomorrow and see what apps have come out of the hackathon, which should be starting in a few hours from now!

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Mobile phones, location and indexing the real world

Mobile phones are rapidly becoming powerful data acquisition devices, as described e. g. in recent (and good) articles in The Economist and Nature. Many phones have cameras, GPS systems and net connections, and some of them sport accelerometers, which can be used to measure the amount of calories burnt by the user, or even to track earthquakes.

A number of enterprising researchers have started to mine the location data that can be obtained from mobile phones (through information from mobile towers routing the communication). Last year, the complex-networks guru Albert-László Barabási and co-workers published a paper, Understanding individual human mobility patterns, where they studied movement trajectories of 100.000 (anonymized) mobile phone users. The result reported by the authors – that human movement is not random but shows high spatial and temporal regularity – was perhaps not as impressive as the sheer size of the data set.

For those who would like to try their hand at analyzing mobile phone data, MIT’s Reality Mining project provides an interesting and freely accessible data set. In this project, students carried (Nokia) phones and their trajectories were tracked. The subjects also answered various questions about themselves and their habits. The data gathered for the Reality Mining project included location information (again, through mobile towers), communication data (call records) and proximity data (using Bluetooth).

The researchers behind the project developed algorithm for extracting routine everyday patterns from user’s lives and claim they can predict their subjects’ next actions to a fairly good approximation.

The Economist article linked above quotes one of the MIT researchers, Alex Pentland, as saying that “… some handsets can capture information about individuals, such as their activity levels or even their gait, using built-in motion sensors.” This suggested to me that it might be possible to detect changes in gross motor patterns in an individual, such as those that have been shown to sometimes occur in depressed patients. Thus, a smart phone could be an “early warning system” for depression.

The Reality Mining group has spawned off a company, Sense Networks, that aims to bring location-based data to the commercial sphere in a big way. Their slogan is “Indexing the real world using location data for predictive analytics.”

Indexing the real world! Now that would be something.

Currently, Sense Networks offers a service, CitySense, for finding out where the action is in a city. I quote from the web site:

Citysense passively “senses” the most popular places based on actual real-time activity and displays a live heat map. The application intelligently leverages the inherent wisdom of crowds without any change in existing user behavior, in order to navigate people to the hottest spots in a city. […]

The application learns about where each user likes to spend time – and it processes the movements of other users with similar patterns. In its next release, Citysense will not only answer “where is everyone right now” but “where is everyone like me right now.” Four friends at dinner discussing where to go next will see four different live maps of hotspots and unexpected activity. Even if they’re having dinner in a city they’ve never visited before.

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