First, a special thanks to our hosts Cindy Hanson and Colin Kelly of Smart Design who not only provided us with a spectacular space but treated the group to some very smart snacks and drinks. They are doing some great work humanizing technology in fields like aging and healthcare and they also design all those great OXO products.Tracking To Meet Goals
Bethany Soule showed us her pet project Kibotzer.com, a tool that lets people track their progress toward all sorts of goals. The first graph was autogenerated from data collected at her computer using a few time tracking sites including Rescue Time and Slife Labs. The next graph was weight data generated from her Withings WiFi body scale. At the end she showed us an example mashup of Kibotzer and EtherPad being used by a couple of folks to write a novel for the National Novel Writing Month or NaNoWriMo. (Bethany's presentation on Vimeo)Your Every Move
Josh Schiffman walked us through a couple of demonstration projects that were built using the Xtify API. There's SeeMyWhere which shares your phone's location to record where you are right now and there's MyEveryMove which is more of a diary of where you've been and where you've spent your time. Xtify is building these apps to find out if we can learn something interesting about ourselves once we know how we spend our time and energy. (Josh's presentation on Vimeo)
Things We Can't Measure
Dan O'Sullivan walked us through a fascinating class he teaches at NYU-ITP called "The Rest of You" where students try and quantify things that are more unconscious and less intentional. Dan talked about how we all operate under the illusion that we're seeing everything when in fact we're only seeing a small slice of reality. How do we get around seeing things that we can't measure? To understand ourselves better, how do we quantify those missing things?One husband and wife team tracked their galvanic skin response as they watched a movie together. They discovered that their responses were very different at points in the movie but also very similar at other times. (Dan's presentation on Vimeo)
What Did You Have For Lunch 2 Days Ago?
Sam Huleatt, Mike Singleton and Eric Friedman showed us their dead simple, lightweight tool called Eat.ly for tracking what you eat by using your phone's camera and email. Take a picture of what you're eating and email it to post@eat.ly --if you see what you ate 2 days ago, it could have an impact of what you decide to eat today or tomorrow.Lots of good suggestions from the group about measuring emotions at the same time, sharing your visual food diary with a nutritionist and so on. A great tool, check it out. (Sam, Mike and Eric's presentation on Vimeo.)
Your Personal Genome
Esther Dyson, a volunteer in the Personal Genome Project, shared with us her personal genome on 23andMe, a company that genotypes your DNA. What was particularly interesting was a new feature that 23andMe is rolling out called Relative Finder which lets you find people with whom you might share a small section of a genome. (Esther's presentation on Vimeo.)Although we ran out of time, we will have Garfield back to present self quantifying iPhone apps and Google spreadsheets implementations and David Roddenberry from HealthyWage, a company that pays people to lose weight.
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How it works
Taking Twitter as the backdrop, and the #hash being the first example, Microsyntax might be termed 'in-line metadata'. It is a self enclosed tag that associates this post with other like tagged posts. It helps search, and it helps set context and find-ability.
The first version of OHME adds more meaning to a set of personal metrics, including blood pressure, weight, steps per day, pain, and about 20 metrics a person can log using SMS, Twitter, devices, or nearly any tool that sends messages. The project offers royalty free libraries for schemas and parsers.
Where it fits in today (person to machine)
When micro-blogging, or posting personal status, hashes can be used to help systems (machine readable) tools use these tags and syntax to facilitate actions. For example, posting #spd=13045 suggests that a person has walked the equivalent of 13,045 steps in this day.
With microsyntax there is a new dialog on how to aggregate device manufacturers, software vendors, and users to grow a vocabulary that thrives and rewards them with good tools and increased connection to their community.
Where it leads in future (machine to machine)
The advent of microsyntax, and OHME provides a new rhythm to the stream. Mashups made from diverse streams of personal data allow new contexts to emerge, and new possibilities for action and specialization. How will the health care system respond? Will it become more patient centric, or merely use data generated automatically by various devices to make us more "hospital ready?" Microsyntax such as the OHME project highlight the opportunity for every person to have quality streams of personal metrics. Health loggers are already using microsyntax today. Now is the time to build tools that aggregate and share these streams in meaningful ways.
Some considerations (machine to person is person to person)
In observing the landscape, it looks promising that natural alliances can form around syntax and vocabularies, giving rise to tools that support each other's streams and have graceful hand-off from system to system. In this new world model of data stewardship, a future can be seen where the microsyntax stream becomes more a critical resource. It is in this context that enterprise class systems may emerge to help guide microsyntax systems towards reliable services.
Today, our social web may be a bit fragile for such un-fettered live results about personal metrics. A community designed sandbox for moving services gradually into the consciousness and letting first-adopters set the terms is a promise for microsyntax.
Even though it is easy to type #911 #Robbery, our social and operational systems may not be as easy to accept the consequences of the message until we set rules and contexts of reliability - and the sender is authenticated in a way that grows trust.
In this arena, microsyntax has both the honor of being extremely easy for the user (can do it without a mouse or selection) and to locate (parsers and search ala Twitter). It also on the cutting edge of personal utility and personal safety and asks the question of how do we communicate personal streams.
Speaking for one logger, this is a great step forward, the start of an the ecosystem that supports people and patients everywhere. #OM+1!
Disclosure: Mike Kirkwood's first post on Quantified Self, he is CEO of Polka a personal health platform. 
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New York area QS readers should drop by the NY Quantified Self Show&Tell#3 tonight at Smart Design. Steve Dean, who launched the New York meeting, has a great program lined up. Here's his description, from the New York QS Meetup site. If you join the New York MeetUp, you can RSVP, and you will be notified of future meetings as well. Here's Steve's description of tonight's meeting: I'm looking forward to seeing you at our next Show&Tell. As in the past, we'll start presentations at 7pm. Each presenter gets about 12 minutes to tell everyone about their self-tracking project, what they are learning and what tools they are using. If you're free earlier, join us from 6-7 for a social hour. We're meeting at Smart Design (below).Have fun, New York QS'ers and I look forward to hearing more about the talks.
RSVP now:
http://www.meetup.com...
We have a great lineup planned:
- Bethany: tracking anything you can put a number on at kibotzer.com
- Josh Schiffman: Tracking "myeverymove" using his persistent location beacon
- Dan O'Sullivan: Examples of student projects from ITP/NYU
- Dierdre O'Brien: a self-tracking project from 1973-74 tracking M&M color count data from a vending machine
- Sam Huleatt, Mike Singleton & Eric Friedman: tracking meals with Eat.ly
- Joe Dizney: an update on his Ben Franklin project / quirky metrics
- Esther Dyson: 23andMe, Personal Genome Project & Keas
- Amy Drill: Personal relationships
And you can always sign up to present when you arrive.
Our friends at Smart Design have offered to host us at their place 601 W. 26 St, Suite 1820, between 11th and 12th Aves. You will need to show photo ID to enter the building and at Smart you'll sign a short confidentiality agreement.
See you tomorrow!
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The QS Show&Tell #9 was very fun and interesting. Here is a quick recap with links. We met at Stanford courtesy of Martha Russell of Stanford's MediaX, and the evening began with Martha's intro to her program, which links visionary research to industry applications. A list of fall seminars at MediaX shows a bit of what they are up to. The seminars are open to the public, and full of interesting things for QS types. Martha hosted as at the Wallenberg Hall Learning Theater, a great experimental learning space with high walls, three projection screens, and balcony viewing.
Steve Brown's presentation of 3banana came at a more fair and leisurely pace than at the last meeting, where he was stuck at the end of a long night of talks. Steve was the creator of Health Buddy, a pioneering self-tracking system, which he sold to Bosch Healthcare. 3banana is a more general tool, and Steve talked about his goal to augment human intelligence through giving us access to more efficient external memory. Steve's talk showed a couple of self-tracking trends we've already noted coming together, including SMS as a tracking lingua franca and structuring data with hashtags.Mark Carranza gave an update on his Social Memory Experiment, first presented at a QS last December. He is working toward taking his personal memory tracking system and releasing it as a social app, and invited all interested parties to help. More on Mark's interesting work can be read here at this earlier post: The Social Memex.
We got to meet Margie Morris, the inventor of the "mood phone" in person, as she was visiting the Bay Area. Margie's work was described in an earlier QS post: The Mood Phone and the Circumplex Model. Trained as a clinical psychologist, she is a senior researcher at Intel's Digital Health Group. She played us some excerpts from videos with users discussing possible applications. One of the users in the video, a male working in a technical field, explained to the interviewer his practice of concealing his mood in order to avoid conflict, and speculated about the usefulness of a technical system to reveal actual emotional states. This provoked some interesting discussion of the social dimension of mood tracking.
Alexandra Carmichael invited everybody to take advantage of the stellar QS Scientific Advisory Board. These are professional researchers who are willing to field questions about self-tracking and self-experiment, which Alex will collect and transmit. The questions and answers will be published here, so that others can take advantage of the advice. Experiment design, statistical analysis, or other topics are welcome. Alex published her invitation on the blog a few weeks ago, in this post: Introducing the Quantified Self Advisory Board! Take a look at it and see the excellent resources available to you.Brian Mossop, who blogs at The Decision Tree, a blog about predictive medicine and the future of healthcare, presented an idea for a new smoking cessation company, that gave smokers a decreasing "budget" of cigarettes and rewarded them with permission to smoke cigarettes (withing the budget) when they met exercise or other goals. Brain's father was a smoker, and he suspects that methods of self-tracking and simple rewards, plus some social encouragement, will be helpful to people trying to quit.
Finally, Robin Barooah showed the results of his coffee and concentration self experiment. He posted here about it already. (See: The false god of coffee.) His post was widely linked, with mentions on BoingBoing, Hacker News, and Freakonomics, and is now the most commented post on QS. Thanks Robin for a great post!
This year I decided to stop drinking coffee, my only source of caffeine. Anyone who knows me will recognize this as a radical step. I've been drinking coffee since age 10, and I'd developed quite an obsession for the perfect cup.
In the past, I've experimented with quitting a few times by simply going cold turkey. Each time, the physical withdrawal, basically headaches, was over within 10 days, but after a month or two I would become convinced that coffee was good for my concentration and start drinking it again.
My reason to quit this time was the growing suspicion that coffee was causing mood swings and crashes that are bad for my overall sense of well-being. For this experiment I decided to stop very gradually. I thought that if I allowed the psychological withdrawal to occur gradually alongside the physiological, I would be able to observe my 'coffee-desire' without acting on it, and learn the skill I would need to avoid relapsing in future.
I made the same amount of coffee each day, using a vac-pot. Although I didn't measure caffeine content, I did control many factors including grind, age of beans, water temperature and water/coffee contact time. From this controlled pot of coffee, I used measuring cups to discard an additional 20ml per week. I used notebook software to keep some records of my progress and I started with a 3 cup pot in mid-April '09. Towards the end of July I wrote "I am increasingly wanting to abandon this project altogether", but I continued and on 8th August I was down to a half shot glass per day, and decided I was done.
I made the same amount of coffee each day, using a vac-pot. Although I didn't measure caffeine content, I did control many factors including grind, age of beans, water temperature and water/coffee contact time. From this controlled pot of coffee, I used measuring cups to discard an additional 20ml per week. I used notebook software to keep some records of my progress and I started with a 3 cup pot in mid-April '09. Towards the end of July I wrote "I am increasingly wanting to abandon this project altogether", but I continued and on 8th August I was down to a half shot glass per day, and decided I was done.
Over the past few days (starting around 12th Oct), I noticed myself increasingly thinking "I am having trouble concentrating and coffee might help". These thoughts came to a crescendo on Wednesday. This time, I was armed with data.
As part of a separate experiment, I have been keeping track of the amount of time I spend working on projects. I work in 25 minute intervals which I time with a coffee timer, and I mark an X in a paper journal for each interval that I successfully complete. If I get distracted, I don't mark the X, and if I can't concentrate, I abandon it and don't mark an X rather than sitting out the timer. I've been doing this since the end of June, so I tabulated the data and created a graph* of my hours of concentration per day, and overlaid a bar showing when I drank my last coffee.
Causality is a complex issue. Obviously this is an n=1 experiment and I am intentionally doing other things that may well be improving my concentration, but one thing is very clear; the amount of time I spend concentrating has not deteriorated since I quit coffee, so I can easily reject the hypothesis "I need coffee to help me concentrate."
I see this as a success for self-quantification. Whether or not it provides a general insight into the effects of caffeine, it validates the utility of self-tracking for making individualized personal decisions.
I will be doing more experiments.
*At the QS MeetUp someone correctly pointed out that I had an error in the labeling of my x-axis on the chart I showed there. This meant that I'd placed the "quitting bar" in the wrong place - near to september 4th, happily this doesn't affect the conclusion, and the graph shown here is the corrected version.
]]>We've gathered an amazing Quantified Self Scientific Advisory Board to be part of our community. It's a star group of international scientists involved in data analysis, data visualization, and self-experimentation. In alphabetical order, they are:
- Alex Bangs, Human Predictive Biosimulation, Entelos
- Gordon Bell, MyLifeBits, author of Total Recall, Microsoft Research
- Jeff Heer, Collaborative Data Visualization and Flare/Prefuse, Stanford
- Gary King, Quantitative Social Science and n=1 experiments, Harvard
- Teresa Lunt, Director of Computer Science Lab, PARC
- Seth Roberts, Self-Experimentation guru, author of Shangri-La Diet, Berkeley and Beijing
- Neil Rubens, Data Mining, University of Electro-Communications, Tokyo
The experiment we'd like to do is to encourage Quantified Self members to formulate questions about the personal data that they are trying to work with. Post them as comments or send them to me. We will make sure the questions are interesting and at least partially answerable, pass them along to the appropriate Advisor, and publish the questions and responses here on the Quantified Self blog, as a way to get discussion going and add value to everyone involved.
So let us know what you think, and start asking questions!
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As in the past, this is a user-generated evening of presentations by folks who are self-tracking in one form or another. Each presenter gets about 12 minutes to tell everyone what they are learning and what tools they are inventing.
I was unable to attend the last show and tell because it came during the final weeks of my overdue book deadline (which is now past me!). But Gary Wolf and I will be co-hosting this one, and filming the talks. If you are around the Bay Area go over to the QS Meetup page to get directions and let us know you are coming. I heard the last meeting was swamped, so we'd like to be more prepared this time. (We WILL post the talks from last meeting.)
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Gilles
Chatellier, 'Feasibility Study of N-of-1 Trials With Blood Pressure
Self-Monitoring
Hypertension, 25 (2): 294 - Hypertension
Hypertension, 25 (2): 294 - Hypertension
I measure blood pressure at home. Unfortunately, it is easy to become bored with this procedure, and neglect it. In fact, it is more fun to wonder why measuring blood pressure is so boring than actually measuring blood pressure, so of course that's what I've been spending some of my time on lately. My guess is that part of the problem is that home blood pressure measurements vary a lot. I've had single sessions in which my systolic ranged 11 points and my diastolic 16 points. This measurement range is larger than the likely effect of any intervention I'm going to be making. Therefore, a single measurement session doesn't give me the feeling that I'm adding any information. It's frustrating and stupid. Damn measurements.
Of course a good way to track measurements with a lot of random error is to use a moving average. So here's the question: how many blood pressure measurements does it take to get results that accurate enough to discern the effects of treatment? Here is a graph from a paper published in Hypertension that suggests an answer. I won't break down the method here. There is a link to the paper at the bottom of the graph and you can explore it for yourself. The quick version is that researchers compared the difference between two series of measurements taken at home, varying the number of measurements in the series, and watched the difference decrease as the number of measurements went up. The graph shows a nice, smooth decrease in variation. You achieve 80% of the total drop in variation after 15 measurements.
In other words, if you take three measurements per day, you can get a decent baseline for blood pressure experiments in five days. This seems like good news.
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1. FitBit ships
At long last! FitBit, the accelerometer with the beautiful clip-on form factor and wireless uploading of exercise and sleep data, has arrived. A one-time fee of $99 puts passive motion tracking in your pocket.
2. DailyBurn launches FoodScanner iPhone app
Tracking your fitness and nutrition is going mobile. DailyBurn has a $0.99 iPhone app that lets you take pictures of the barcodes on foods you eat, helping you more smoothly track your caloric intake.
3. Gordon Bell and Jim Gemmell release Total Recall book
Based on their experience with the MyLifeBits project at Microsoft Research, Bell and Gemmell wrote Total Recall: How The E-Memory Revolution Will Change Everything. They talk about the future implications of being able to remember everything about your life in delicious detail.
These are definitely exciting times to be a Quantified Self enthusiast!
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There was also a competition for ideas that would change the future of healthcare. I entered this competition using self-tracking as a topic, and was one of 3 winners! Here is the 5-minute talk I got to give to 500 healthcare change agents at the Mayo Clinic, and the written summary that won the competition.
Click here to watch this talk
"The New Wave of Self-TrackingUbiquitous, invisible biosensors. Constant, streaming measurements. Analytics for your health.
Detailed self-tracking will transform our understanding of our bodies, our health, and our medicine. Geeks are already tracking everything from calories to blood pressure to steps taken during the day (Quantified Self). People with chronic conditions track their treatments, pain levels, and side effects (CureTogether).
Click here to watch this talk
The ultimate promise when this goes mainstream is true personalized medicine, where each person gets a treatment plan individual to their body. It's an exciting future, and the seeds are being planted now."
Attila Csordas talked about posting his 23andMe data, one SNP at a time on twitter. Attila said this was a "failed experiment" due to the limitations of the twitter service; for instance, twitter doesn't like to see lots of similar posts, and tends to interpret them as spam. But the idea of treating the genome as a person information stream, along with the notion of SMS as a common transfer protocol for data normally considered sensitive and private, were just a couple of interesting points from the discussion that followed. Another great comment: instead of making the human the account holder, what about making the SNP the account, allowing each SNP to have its own followers.
Gopal Sarma talked about the limits of memory, using anecdotes of Renaissance masters who used techniques of visual association. Wikipedia has a good article on "the art of memory," that describes these techniques. An accessible popular account can also be found in The Art of Memory, by Frances A. Yates. The image to the right of a fortified city on a hill is taken from the literature on the art of memory. You can learn more here. Sri Srinivasan showed us his self-tracking web site, Facet of Life. With Facet of Life, you can schedule regular alerts and reminders via SMS, email, and the web. When you reply to the message with a word or a number, it is entered into a database, and Sri is building tools to aid understanding. Sri, who suffers from chronic pain, talked about some of the knowledge he had already gained from using the tool; for instance, visiting the gym reduces pain, even when the session is brief. He used to skip the gym if he wasn't going to have time for a full workout, now he goes even if he only has a few minutes.
Can estimate suicide risk by counting words? Bill Jerrold talked about the quantitative analysis of natural language. After a general introduction to the notion of forensic linguistics by way of Don Foster's work, he reviewed some recent findings that psychiatric conditions can be identified based on subtle linguistic abnormalities, and that this process can be automated using speech recognition software. His talk raised the interesting prospect of quantitative self-monitoring via recordings of everyday speech and writing. (Here are two interesting papers Bill mentioned: "Word Use in the Poetry of Suicidal and Nonsuicidal Poets" and "Language use of depressed and depression-vulnerable college students.")
Esther Dyson described her own use of the 23andMe personal genotyping service. Giving us a quick tour of her own genome, she mentioned that she especially appreciates looking at the graphs that compare the genotype of various members of her family. She said the immediate practical benefit of the personal genome was - for the moment at least - very slight and that people who are using the service at this point are playing a role as benefactors, contributing to a critical mass of data that can lead to new discoveries.
Joe Betts-Lacroix revisited "Joe's Dream," his vision an easy method of entering and retrieving personal data. Since he gave this talk, barely a year ago, several features of this dream have been realized. So he proposed another step that he called "personal instantaneous feedback." (The video above is Joe''s original talk last year, at QS Show&Tell #2.)
Bo Adler works at Fujitsu labs, where his work involves collecting and processing medical sensor data. Bo is also a walking experiment. He showed us how he does constant monitoring of his heart rate, blood oxygenation level, and blood pressure, using wearable sensors, and then showed us the results of one of his self-experiments. He suffers from sleep apnea, and uses a variety of methods to combat it. By graphing his biometrics during sleep, he learned - among other things - that while taking Nyquil made him feel that he was sleeping better, his data told a different story.Mark Carranza gave us a quick recap of his MX "memory experiment," which he described more fully at QS Show&Tell #3.
Finally, Steve Brown gave a too-quick talk about "augmenting your brain," and about 3banana, a system he's created for enhancing working memory. We were out of time, so he is going to come back again. If you can't wait, however, the slides are here.
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Steve is the founder of a company called 3banana. He talked about augmenting the brain through enhancing working memory. When he returns, some QS folks may also want to ask him about his last company, Health Hero, a pioneer of self-monitoring that was acquired last year by the Bosch Group.
Thanks again to everybody who showed up on Monday night!
For this meeting, we return to the spacious, comfortable, and conveniently located offices of our generous friends at the Institute for the Future in downtown Palo Alto. IFTF is a few steps from the Caltrain stop, across from the main entrance to the Stanford campus. For full details, check out our Quantified Self MeetUp page.
As usual, we will have a social hour from 6 p.m. to 7 p.m., start the talks promptly at 7, and end by 9.]]>