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Archive for the tag “self-tracking”

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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Identifying migraine triggers and “your genome has a posse”

MyMigraineJournal is an interesting self-tracking site with some statistical weight behind it. The idea is to let migraine sufferers define potential “triggers” of migraines, like red wine or aged cheese, after which they will complete a daily questionnaire about what they ate, drank etc. and whether they had a headache that day (this takes about 3o seconds per day). The site will also try to assess whether any of the triggers seems statistically related to higher (or lower) migraine risk. As outlined here, this is done through logistic regression on one variable (trigger) at a time. The site uses a hierarchical Bayesian model where the prior distribution is initially uniform but will eventually, after enough data has been collected, be derived from the aggregated population of previous users, which I think is a nice touch. They don’t look for interactions between triggers yet, but may add such functionally in the future. A user can download their own complete data in Excel format, or delete some or all of it from the system. I think simple but clever systems like this could prove quite useful to people.

On a related note, Nature Medicine recently ran an interesting article, “Personalized investigation“, about people who use direct-to-consumer genetic tests to learn more about genomes and physiology. The article describes how five early adopters of 23andMe’s SNP tests teamed up to investigate whether SNPs in a gene coding for an enzyme related to vitamin B metabolism were predictive of how the carriers would respond to vitamin supplements. The team then performed a series of experiments where they either took no supplements, took multivitamins, L-methylfolate or a combination of both multivitamins and L-methylfolate. After each phase of the experiment, they took blood tests to measure homocysteine, a biomarker for vitamin B activity.

Now, unless I’m misguided or the news is misreported, such an experiment with five subjects could never get anywhere close to a statistically significant outcome. But with larger cohorts, that could change. A new company called Genomera is developing tools that will allow this kind of self-experimentation study to scale into large numbers of participants. In fact, the Nature Medicine article says that Genomera will “roll out the vitamin study as the first open participatory project under its platform.” As of now, the Genomera site still appears to be mostly under construction, although it does say that the company has trademarked “Your genome has a posse” and related phrases. It sounds like an interesting business concept – I just wish they hadn’t described it as “the Facebook of genomics” in the Nature Medicine article …

Surprising self-experimentation

Seth Roberts, a pioneer in self-experimentation, has written an extremely interesting article called “The unreasonable effectiveness of my self-experimentation”  [PDF link]. In it, he tries to explain why his self-experiments were, in his opinion, so much more successful than a lot of conventional research. As he puts it himself in the paper:

[…] I was not an expert in what I studied and my research cost almost nothing. I did it in my spare time. In spite of this, my self-experimental research was far better than my mainstream research […]

Roberts describes how he started with self-experimentation by counting his pimples every day and trying a treatment to get rid of them. Eventually, he would discover surprising facts about himself, for example that drinking sugar water would tend to make him lose weight, and that eating breakfast would tend to make him wake up too early (but that standing up a lot would make him wake up later.) One of the main reasons he gives for his success is the freedom from academic pressure:

Myself-experimentation was not my job. For a long time, I did not expect to publish it; even later, after I decided to, I did not plan to use it to gain status within a profession. This freed me to (a) do whatever worked and (b) take as long as necessary. Professional scientists cannot try anything and cannot take as long as necessary. As Dyson […] said, ‘‘In almost all the varied walks of life, amateurs have more freedom to experiment and innovate [than professionals].”

The paper is interesting throughout.

Edit 2/6 2010: I found another paper by Roberts, a 61-page whopper called “Self-experimentation as a source of new ideas: Ten examples about sleep, mood, health and weight“, where he goes into a lot more detail (complete with pretty graphs plotted in R) about his various experiments. Definitely worth a look too.

Viewpoints on self-tracking

Here are some interesting articles on self-tracking published during the spring.

The data-driven life, a very meaty and well-researched article in The New York Times. It’s written by Gary Wolf, who is a co-host of the self-tracking blog, The Quantified Self. Standout quote:

With my spreadsheet, I inadvertently transformed myself into the mean-spirited, small-minded boss I imagined I was escaping through self-employment.

An interview with Nicholas Felton, who publishes a “personal annual report” crammed with visualizations of data he has collected about himself. Standout quote:

I think it would be more accurate to say that the age of the illusion of privacy is over. Your activities have long been transparent to credit card, mobile phone operators and others… now we have been given the tools to reveal this information socially (intentionally or unintentionally).

Numbers from the heart, a highly interesting essay by professor Ramesh Rao, who has done some heavy-duty signal analysis of his heart rate variability while meditating, running and sleeping, amongst other things. Standout quote:

The irony of getting attached to a practice that teaches detachment got me to take a look at Poincare plots of different styles of Yoga.

The essay also includes an interesting passage about entoptic phenomena (visual phenomena generated “internally” by the nervous system.)

Why I stopped tracking by Alexandra Carmichael is a powerful reminder of the potential drawbacks of self-tracking.

Peer-reviewed life?

For those curious about where self-tracking (or self-measurements/self-monitoring/personal informatics, or whatever we should call it) might be going in the future, it could be worth glancing through the papers from an interesting workshop, Know Thyself: Monitoring and Reflecting on Facets of One’s Life, which was held in Atlanta in April. The papers have intriguing titles like Life-browsing with a Lifetime of Email, Computational Models of Reflection, Collaborative Capturing of Significant Life Memories and From Personal Health Informatics to Health Self-management. A striking quote from a paper entitled Assisted Self Reflection: Combining Lifetracking, Sensemaking, & Personal Information Management by Moore et al:

Just as we are able to submit papers to peer-reviewed con-
ferences and journals, we could anonymously share selected
portions of our life activities for peer or professional consulta-
tion when making major career decisions, learning a new skill
or in the process of recovery. By seeing ourselves through
the eyes of others, we are more able to normalize behavior
patters and raise awareness of suppressed abnormalities.

I’m not sure I am ready for peer review yet … maybe some day…

Video time

Here are a few video clips I’ve enjoyed watching over the past week.

From TEDMED2009, David Agus talks about cancer research and covers quite a lot of territory, from the value of monitoring your habits (he briefly discusses his own Philips DirectLife device) to the need for a molecular rather than tissue-based definition of cancer and his quest to model cancer as a complex system that has to do with a lot more than genetics.

The Argument for Better Health, in 3 Minutes & 53 Seconds is an attempt to summarize the most important arguments of Thomas Goetz’ new book The Decision Tree for a broader audience. In other words, it’s about how individuals can take control of their own health by using what Goetz calls a decision tree approach. The video, although good, is kind of entry-level material; if you want to go a bit deeper, you could download podcasts of the introduction and first chapter of the book. Here are three good reviews of the book.

Finally, a video in four parts explaining the benefits of using the R language for statistical analysis. I use R myself practically daily and think it’s great. These videos make it clear that it has now spread far outside of academia and has become an important part of the data analyst’s toolbox.

Link roundup

Here are some interesting links from the past few weeks (or in some cases, months). I’m toying with the idea of just tweeting most of the links I find in the future and reserving the blog for more in-depth ruminations. We’ll see how it turns out. Anyway … here are some links!

Open Data

The collaborative filtering news site Reddit has introduced a new Open Data category.

Following the example of New York and San Francisco (among others), London will launch an open data platform, the London Data Store.

Personal informatics and medicine

Quantified Self has a growing (and open/editable) list of self-tracking and related resources. Notable among those is Personal Informatics, which itself tracks a number of resources – I like the term personal informatics and the site looks slick.

Nicholas Felton’s Annual Report 2009. “Each day in 2009, I asked every person with whom I had a meaningful encounter to submit a record of this meeting through an online survey. These reports form the heart of the 2009 Annual Report.” Amazing guy.

What can I do with my personal genome? A slide show by LaBlogga of Broader Perspectives.

David Ewing Duncan, “the experimental man“, has read Francis Collins’ new book about the future of personalized medicine (Language of Life: DNA and the Revolution in Personalized Medicine­) and written a rather lukewarm review about it.

Duncan himself is involved in a very cool experiment (again) – the company Cellular Dynamics International has promised to grow him some personalized heart cells. Say what? Well, basically, they are going to take blood cells from him, “re-program” them back to stem-cell like cells (induced pluripotent cells), and make those differentiate into heart cells. These will of course be a perfect genetic match for him.

Duncan has also put information about his SNPs (single-nucleotide polymorphisms; basically variable DNA positions that  differ from person to person) online for anyone to view, and promises to make 2010 the year when he tries to make sense of all the data, including SNP information, that he obtained about his body when he was writing his book Experimental Man. As he puts it, “Producing huge piles of DNA for less money is exciting, but it’s time to move to the next step: to discover what all of this means.”

HolGenTech – a smartphone based system for scanning barcodes of products and matching them to your genome (!) – that is, it can tell you to avoid some products if you have had a genome scan which found you have a genetic predisposition to react badly to certain substances. I don’t think that the marketing video done in a very responsible way (it says that the system: “makes all the optimal choices for your health and well being every time you shop for your genome“, but this is simply not true – we know too little about genomic risk factors to be able to make any kind of “optimal” choices), but I had to mention it.

The genome they use in the above presentation belongs to the journalist Boonsri Dickinson. Here are some interviews she recently did with Esther Dyson and Leroy Hood, on personalized medicine and systems biology, respectively, at the Personalized Medicine World Conference in January.

Online calculators for cancer outcome and general lifestyle advice. These are very much in the spirit of The Decision Tree blog, through which I in fact found these calculators.

Data mining

Microsoft has patented a system for “Personal Data Mining”. It is pretty heavy reading and I know too little about patents to able to tell how much this would actually prevent anyone from doing various types of recommendation systems and personal data mining tools in the future; probably not to any significant extent?

OKCupid has a fun analysis about various characteristics of profile pictures and how they correlate to online dating success. They mined over 7000 user profiles and associated images. Of course there are numerous caveats in the data interpretation and these are discussed in the comments; still good fun.

A microgaming network has tried to curb data mining of their poker data. Among other things, bulk downloading of hand histories will be made impossible.

Existential computing

How cool is this course, called “The Rest of You” and taught at New York University? It was mentioned in a recent blog post at The Quantified Self, which also links to a video of teacher Dan O’Sullivan talking about it.

The Rest of You course is about building tools to quantify your experiences in everyday life, with a special emphasis on unconscious and less intentional things – for example things that are controlled by the autonomic nervous system, like galvanic skin response (which has to do with e g fear, anger and sexual arousal) and breathing. As mentioned in the QS blog, a husband and wife team measured their galvanic skin responses while watching a movie, and compared the readouts afterwards. Mostly the responses were similar, but there were many times where one of them had a strong response while the other reacted weakly if at all.

The syllabus includes questions/assignments/material like:

  • What was your day really like?  Get an objective picture of your day using light, gravity, sound, image, temperature.
  • How are you really feeling? Get reading from unconsciously controlled reactions sweat, breath, temperature, electical, posture, heart, sound, subliminal input,eeg
  • Graphing data in Processing or using Flowing Data , SensorBase, Pachube
  • Using batteries, small microcontrollers, how to make the devices fit on your body, keylogging, and how to get data from a phone
  • Reading about flow and mirror neurons

It sounds excellent already in theory, but looking at some of the students’ blogs really drives home how cool it is. For example, John Kuiphoff wired himself up and devised an experiment for quantifying how well wrist braces (which he got for his carpal tunnel syndrome) stabilize movements during typing. He also did an interesting experiment about how well people can distinguish subtle variations in color. Elizabeth Fuller fitted her cocktail dress out with a proximity sensor and an accelerometer and sent data from the dress onto a computer during a party.

Apart from the tech/data aspects of the whole thing, I like Dan O’Sullivan’s idea about “existential computing”, as he calls it – to use these tools to realize that our conscious experience is actually just a small slice of the sum total of what we go through. The writing assignments pose tough questions about illusions and happiness: What are the some illusions in my existence? How do they affect your happiness? Can new technologies correct for these illusions? Can gaining insights with a more complete view of your existence improve your life?  Can it make society better?

… but does it work?

Upon learning about the possible future of medicine, including self-tracking and social networks for patients, you might wonder whether these things really work or if they are just nice ideas. Well, now there are at least some indications that they are useful.

The Decision Tree quotes a report from the the Kaiser Permanente Center for Health Research which says that people who kept track of how much food they ate lost twice as much weight as people who didn’t in a study about weight loss. As a press release puts it, “It seems that the simple act of writing down what you eat encourages people to consume fewer calories.” The study was published in the American Journal of Preventive Medicine in August. However, the effect is much more powerful if people exercise and self-track together, in line with ideas about “social contagion” that I have discussed before.

(By the way, the last several posts at The Decision Tree about the Health2.0 conference and the Kaiser Permanente’s HealthCamp “unconference” make for interesting reading about everything that is brewing in this field.)

What about “social medicine”? A couple of weeks ago, Alexandra Carmichael from CureTogether gave a talk at the Mayo Clinic and revealed that the company has achieved its first statistically significant finding based solely on self-reported data from users of their site. According to these “patient-generated data”, people with infertility are twice as likely to have asthma. This has also been found before in controlled clinical studies. It’s a sign that aggregated self-reported data has the potential to uncover many known and unknown correlations.

On the theme of patient data, there is a new piece, Owning Your Health Information – An Inalienable Right by Leslie Saxon, which is worth a read.

And a final reading tip: a Nature opinion piece (with Craig Venter as one of the authors) called An agenda for personalized medicine. It discusses how disease risk assessments obtained from two direct-to-consumer genetic testing companies can vary quite a lot in some cases. The authors suggest a number of “best practices” to improve disease risk predictions.

Body computing, preventive, predictive and social medicine

There have been many interesting articles and blog posts about the future of medicine, and specifically about the need to automatically monitor various physiological parameters, and, importantly, to start focusing more on health rather than disease; prevention rather than curing. The latter point has been stressed by Adam Bosworth, the former head of Google Health, in interviews like this one (audio) and this one (video, “The Body 2.0”). Bosworth is one of the founders of a company, Keas, that wants to help people understand their health data, set health goals and pursue them. He has a new blog post where he talks about machine learning in the context of health care. He (probably rightly) sees health care as lagging behind in adoption of predictive analytics. But he thinks this will change:

All the systems emerging to help consumers get personalized advice and information about their health are going to be incredible treasure troves of data about what works. And this will be a virtuous cycle. As the systems learn, they will encourage consumers to increasingly flow data into them for better more personalized advice and encourage physicians to do the same and then this data will help these systems to learn even more rapidly. I predict now that within a decade, no practicing physician will consider treating their patients without the support/advice of the expertise embodied in the machine learning that will have taken place. And finally, we will truly move to an evidence based health care system.

Along similar lines, the Broader Perspective blog writes about the “three tiers of medicine” that may make up the future healthcare system. The first tier consists of automated health monitoring tools that collect information about your health, The second tier is about preventive medicine and involves “health coaches”, who “…incorporate genomic data, together with family history and current phenotype and biomarker data into an overall care plan“. Finally, the third tier is the traditional health care system of today (hospitals, doctors, nurses).

I learned a new term for the enabling technology for the first (data-collection) tier: body computing. The Third Body Computing Conference will be hosted by the University of Southern California on Friday (9 October). The conference’s definition of body computing is that

“Body Computing” refers to an implanted wireless device, which can transmit up-to-the-second physiologic data to physicians, patients, and patients’ loved ones.

A new article about the future of health care in Fast Company also talks about body computing and predictive/preventive health care:

Wireless monitoring and communication devices are becoming a part of our everyday lives. Integrated into our daily activities, these devices unobtrusively collect information for us. For example, instead of doing an annual health checkup (i.e. cardiac risk assessment), near real-time health data access can be used to provide rolling assessments and alert patients of changes to their health risk based on biometrics assessment and monitoring (blood pressure, weight, sleep etc). With predictive health analytics, health information intelligence, and data visualization, major risks or abnormalities can be detected and sent to the doctor, possibly preempting complications such as stroke, heart attack, or kidney disease.

Although the article is named The Future of Health Care Is Social, it actually talks mostly about self-tracking and predictive analytics. It does go into social aspects of future healthcare, like online health/disease-related networks such as PatientsLikeMe or CureTogether. All in all, a nice article.

And finally (if anyone is still awakw), it has been widely reported that IBM has joined the sequencing fray and are trying to develop a nanopore-based system, a “DNA transistor”, for cheap sequencing. There are now several players in this area (for example, Oxford Nanopore, Pacific Biosystems, NABSYS) and some of them are bound to lose out – time will tell who will emerge on top. Anyway, the reason I mentioned this is partly that IBM explicitly connected this announcement to healthcare reform and personalized healthcare (IBM CEO also wants to resequence the health-care system) and partly because of the surprising (to me) fact that “[…] IBM also manages the entire health system for Denmark.” Really?

By the way, a good way to get updates on body computing is to follow Dr Leslie Saxon on Twitter.

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