Tag Archives: qstop

Rosane Oliveira on The Quantified Double Self

Rosane Oliveiria is a researcher and scholar that focuses on integrative medicine, genomics, and nutrition. She’s also an identical twin. In 2012 she was struck by the different patterns of weight fluctuations that she and her sister, Renata, had been experiencing. Using historical data and medical records she was able to go back in time and track their paired histories, dietary changes, and blood markers. Rosane and Renata started adding to there data-rich story by exploring genetic testing, additional biomarkers, and are looking to incorporate activity and microbiome data in the future. Watch her presentation, from the 2013 Quantified Self Global Conference, to learn more about this interesting quantified double self story.

Posted in Conference, Videos | Tagged , , , , , , | Leave a comment

Fit Fifties, Sound Sixties: Maria Benet on Active Aging

Maria Benet began tracking her activity a few years ago as a way to lose weight and take control of her health. What started with a simple pedometer and a few custom Access databases has morphed into a multi-year tracking project that includes news apps and tools. Her progress and data has even spurred her on to new experiences and athletic endeavors. Watch her talk, filmed at the Bay Area QS meetup group, and read the transcript below.

(Editors Note: We’re excited to have Maria attending the 2014 Quantified Self Europe Conference where we hope to hear an updated version of this wonderful talk.)

What did I do?

Hi, my name is Maria Benet and I am happy to tell you that only about two-thirds of me is here to talk about my tracking project. I mean that literarily, because in the 10 years since I’ve been self-tracking I lost over 50 pounds while getting fitter.

In my early 50s, I was overweight, out of shape, with bad knees, and when not cranky, depressed. I was already on meds for high blood pressure and was looking at the prospect of more prescriptions down the road.

So, what did I do to change my situation? I set about tracking my activity levels, my weight and my food intake with the help of apps, wearable devices – plus — in databases and Excel spreadsheets that I designed. Until late 2011, I tracked inconsistently, but once I discovered mobile apps and wearable devices — I became more systematic and consistent about tracking weight, food intake, and fitness data.

How did I do it? 

When I first started — losing 50 pounds seemed daunting, but going for a walk at least 5 days a week seemed less formidable. To track walks I was going to take in the hilly neighborhood where I live, I created a simple Access database.

I bought a pedometer, hiking shoes, and off I went. After walking, I recorded the duration, the number of steps, and calculated the distances I covered. I also charted my routes by naming the streets, and made notes about the weather and my mood during the walk.

Recording the data turned out to be a form of reward in itself. At the start of this tracking project, I enjoyed seeing the database grow a little more than I enjoyed the actual walks themselves.

Over time, the walks got longer, steeper, and eventually included actual hikes. I also took up the practice of Yoga regularly, and then added Pilates to my exercise repertoire.

Along the way, I also started to lose weight. Though I didn’t weigh myself every day, I began to pay attention to the kinds of foods I ate and tried to wean myself off processed foods in general.

They say you get fit in the gym, but lose weight in the kitchen. In September 2011, when I discovered LoseIt, it became my virtual kitchen: LoseIt helped me see what foods I ate regularly, which of these spiked my weight, even if my calorie intake stayed the same. I noticed these relationships anecdotally, rather than by finding statistical correlations between them.

Tracking in LoseIt helped me realize that as much as I love bread and beer, they are not my friends. Two years ago, an allergist confirmed my wheat sensitivity through blood tests and an elimination diet.

I added Endomondo to my tool box a few months later, since I liked having the maps and stats it offered, in addition to the other data it showed. By December I also added a Fitbit, as with it I could track more accurately how many steps I took and approximate better the number of calories I burned. The Fitbit was like going back to the pedometer, but to one on steroids.

With the Fitibit, I focus mostly on the Very Active Minutes it claims to measure. Increasing that number over time became a game. In 2012, I was averaging about 57 minutes a day, which put me in the 98th percentile. Increasing to 69 minutes only brought me to the 99th percentile, as the Fitbit population also has increased over time.

The Fitbit turned out to be a catalytic tool, because it spurred me on to push the perceived limits of my fitness abilities and possibilities further. It ended up putting wheels under my dreams.

In the spring of 2012,I took up cycling to increase my active minutes and challenge a mental habit of opting out of things because of a fear of failure or thinking of them as not age appropriate. Biking, in turn, added to my collection of gadgets and apps for tracking the metrics involved.

By 2012 then, in addition to LoseIt and Fitbit, I was tracking workouts with a Garmin GPS watch with a HR monitor and my bike rides with a Garmin Edge computer, uploading the data to the Garmin site, to Endomondo and Strava, as each had strengths the other lacked, from my perspective.

To complicate data gathering, back in January 2012, I started a basic Excel spreadsheet that tracks highlights from each of these apps in an application-independent reference for me. In Excel I track the type of activity, duration, distance, if applicable, average and maximum heart rate, Strava suffer points, (a measure of exertion), the hours I slept and how that sleep seemed to me, and additional notes about the day I might think relevant.

The plethora of my gadgets and apps might earn me an entry into the next edition of The Diagnostic and Statistical Manual of Mental Disorders. But exploring these tools was, and still is, my way of looking for a comprehensive and personalized way to track the quantities in my habits and activities that make for a qualitative difference in my life … which brings me to what I learned so far:

What did I learn?

I learned that small quantitative changes in particular daily habits add up to a big difference in quality of life in general.

The incremental additions in my tracking methods and number of gadgets I added produced a lot of data, which I haven’t analyzed closely, because I was already getting a lot of return from them in the form of new experiences in my life.

The most memorable of these experiences is my having completed the metric century ride on the Tour de Fuzz in Sonoma last September. In the space of a little over a year I went from covering barely 8 miles in an hour on my first rides to completing 63 miles in 5 and ½ hours and feeling ready to ride a lot more.

It has been said that motivation is what gets us up and going, but it’s habit that keeps us going. So it is with my tracking: though the motivation was to lose weight, the habit of tracking and keeping an eye on the numbers are what allowed me to go from daily small changes to a much bigger transformation from the overweight, depressed, and achy person I was 10 years ago to who I am now: someone interested in health and fitness and setting goals I can meet.

I learned that for me the act of tracking is the project itself. Although the data I generate can be charted and described in numerical relationships the number that brings me the information that makes a difference in my life, is a simple 1 – or tracking one day at a time.

I love to see the numbers my Garmin and Fitbit generate, but in the end, the quantified self for me is not so much about the measured life as it is about keeping those numbers coming through a well-lived and, more importantly, well-enjoyed life as I go from my fitter fifties into what I hope will be my sounder sixties.

Posted in Videos | Tagged , , , , , , , , | 1 Comment

Joris Janssen on SenseOS

Joris Janssen is a researcher who’s focused his work on combining sensing algorithms with psychological insights. Currently he’s a researcher and developer at Sense Observation Systems, a Netherlands-based company developing context-aware computing. In this talk, filmed at the Amsterdam QS meetup group, Joris gives a brief explanation of the work they do at SenseOS, then discusses Goalie, an app developed to use psychological theory, active and passive sensing, and a therapy gateway to treat and improve depression.

We’re excited to have Joris and his colleague from SenseOS, Jan Peter Larson, joining us at our upcoming 2014 Quantified Self European Conference. If you’d like to learn more about the work Joris and Jan are doing at SenseOS we invite you to register today!

Posted in Conference, Videos | Tagged , , , , | Leave a comment

Eric Jain on Sleep and Moon Phases

Eric Jain stumbled upon a study published in 2013 that found the a full moon was associated with less sleep. Being an avid self-tracker and a toolmaker he decided to find out if that was true for him as well. Eric used his tool, Zenobase, to import, aggregate, filter, and then analyze his sleep data in a few unique ways. While he found some evidence that a full moon was associated with less total sleep he wasn’t able to make any statistically significant results. Watch his short video below, filmed at the Seattle QS meetup group, then take a look at his great screencast where he walks through all his steps to complete this analysis.

Posted in Videos | Tagged , , , , , , | 1 Comment

QS Chicago Meetup Recap

QSChicago_0314

This guest post comes to us from Mark Moschel and Eugene Granovsky, the co-organizers of the Chicago Quantified Self meetup group. At their recent meetup on March 26, 2014 they had three great talks from community members. If you live in the Chicago area why not join the group!

Dan Abreu on GeoTracking
Dan travels a lot. I mean… a LOT! He stepped through an airport well over 300 times in 2012. He started documenting his travel a few years back and has used a variety of tools since: TripIt, Track My Life (discontinued), Google Latitude (discontinued), QStartz, and myTracks. During that time, his technique for tracking evolved and gained complexity. He’s now able to develop very detailed maps of his trips (see below). What has he learned from all this? “Not much” he said. However, he enjoys the practice and consistency of it and is excited to continue finding more uses for this data in the future.

danarbeu_geotracking

Zak Boswell on Sleep
Like many of us, Zak was on a very inconsistent sleep schedule for most of his life and would often stay up too late. However, unlike many of us, Zak was experiencing severe fatigue during the day. In the span of just a couple years, he had 4 car accidents from falling asleep at the wheel (in two, his car was totaled). Realizing this was a problem, he started exploring traditional solutions. He saw a handful of doctors and participated in a very expensive (and ineffective) sleep study. During this time, he also started tracking his sleep and decided to go to bed at a consistent time each day (around midnight). In the data, he saw his sleep quality beginning to improve. He also stopped falling asleep during the day. At first, he struggled with the change, but he’s since changed his whole philosophy and loves it. You can view Zak’s presentation here [PDF].

Ovetta Sampson on how tracking helped her become an Ironman (or “The science of Faith”)
Let’s start with the end on this one. Here’s what Ovetta accomplished: 2.4 mile swim, 112-mile bike ride, 26.2 mile run – all in under 17 hours. Wow! Even more impressive is that she was never an athlete growing up and weighed 270 lbs in 2012. In just a year, she turned a seemingly impossible goal into a real accomplishment. How? She found faith in her data. “Tracking data helped me change my behavior” she said. By tracking her times, weight, speed, and distance, a few things happened: 1) she quickly saw progress and was motivated to keep going, 2) she became competitive with herself, always trying to beat her last score, and 3) she could ignore the thoughts in her mind. As she said, “you have to trust something and the mind is not to be trusted. Trust the data.” Her thoughts kept telling her to quit, but the data proved she was doing well. She didn’t quit and now she’s an Ironman. You can view Ovetta’s presentation here [PowerPoint].

For those of you in the Chicago area Elmhurst Art Museum is hosting a new exhibit called “Lifeloggers: Chronicling the Everyday.” Check it out here.

 

Posted in Meeting Recaps | Tagged , , , , , | 2 Comments

Talking QS for Kids with Sesame Workshop!

grover_sesame

Sesame Street has been teaching kids to count since 1969. It was a big part of my childhood and I always loved it. After all, children get measured a lot: weighed, evaluated, tested. If we adults sometimes wonder how the powerful techniques of quantification can be used for our own benefit, rather than merely serving to strengthen control by others, imagine what it looks like to a kid still learning the basic language of numbers.

Can QS be useful for kids? When we learned that Jennifer Kotler and June Lee, two excellent researchers from Sesame Workshop were planning to be with us in Amsterdam in May at the QS Europe conference, we decided to do a short interview and ask them our question outright.

What is your interest in Quantified Self for young kids?

Jennifer Kotler: What I think is really interesting about the QS movement is that you see data as both an input and an output. Originally I had been thinking about measuring behavior, so we could better understand children’s lives. How do kids use media? Who is around them? That’s akin to ethnographic studies. But when I listened to people talk about quantifying themselves, I realized that data is also a kind of content that informs the self. Kids like to know how they are doing and what they are learning, that feedback is connected to self-regulation. So we are now thinking of Quantified Self data as both an input and an output.

What’s the difference between the way typical media companies might research their viewers and what Sesame Workshop does with kids?

Jennifer Kotler: Our primary mission is to help all children reach their highest potential. We want to help them learn. So we use media as a tool to support child development. We don’t see our media as entertainment only.

When do kids start to care about numbers?

Jennifer Kotler: Even infants have some awareness of mathematical concepts but it is around the preschool age when children are taught about the meaning of numbers more formally. The more socially or emotionally meaningful numbers are in relation to individual children, the more they can learn.

What’s the most interesting research that involves young kids with data?

Jennifer Kotler: There are some small scale ethnographic studies, using a GoPro camera and interviews, but those happen with older children. As Sir Ken Robinson said, a three year old is not “half a six year old.” You can’t take experiences from older kids and just make it easier. You have to ask what is appropriate for kids of that age. We’re coming to the conference to learn about techniques we can use in our research, but also we are also coming in with an open mind and looking forward to absorbing it all!

The Sesame workshop creates media. So what if the results of your research is: kids should have minimal screen time? Could you handle that research result?

June Lee: The big goal of the research we do is not to get people to consume more media, but to improve the media we do make so that people learn more, engage more, and improve their lives.

We can’t wait to see June and Jennifer at our 2014 European Conference in Amsterdam. If you’re interested in combining QS practices with child development and education make sure you register today. We’re only one month away!

QSEU14_small

 

Posted in Conference | Tagged , , , , , | Leave a comment

What We Are Reading

Articles and Posts

Larry Page, TED, and Pooling our Medical Data by John Wilbanks. Health is a hard problem. A problem that people are using data, vast amounts of data, to help solve. This may work, but at the end of the day we have to remember that data is made of people, and those people deserve respect and privacy.

The Loneliness of the Sick Self-tracker by Jane Sarasohn-Kahn. Another great post about the current state of self-tracking and health data for the those trying to manage a chronic condition.

Patients + Providers + Technology = Engagement by Patti Brennan. In this post Patti describes her experience as director of the Project Health Design project funded by the Robert Wood Johnson Foundation and how self-tracking can power a new powerful form of observations of daily living.

Big Data Makes Invisible Air Pollution Visible by Intel Free Press. This short piece explains how community members in Portland, OR are collaborating with Intel Research to understand air pollution by deploying personal connected air sensing devices. Reminds me of the CitiSense project at the University of California, San Diego.

There’s No Such Thing as Gaining a Pound: Reconsidering the Bathroom Scale User Interface by Matthew Kay, Dan Morris, MC Shraefel, and Julie Kientz. Whether you’re using a scale, or hoping to design the next great one you owe it to yourself to read this excellent research paper. The research team examined how people actually us and think about their scales and provides a few design insights they believe could move the field forward.

The Year of the Quantified Self Revolution by Glenn Lubbert. A really wonderful piece a great member of our QS community. Glenn touches on conversations and experiences he’s had as he’s “gone down the rabbit hole” of self-tracking.

Data Scientists by Amelia Greenhall. Is our perception and use of the term “data scientist” a crack in the system? Is that a good thing? Amelia describes her experiences and what she’s thinking about this new class of employee.

You, Your Quantified Self, and all the (non) Quantified Others by Marco Van Hout. In this blog post Marco examines possible (present and future) scenarios for the self-tracking. His focus on how self-tracking and a data collection affects our communal relationships and societal norms is especially interesting.

In Defense of Google Flu Trends by Alexis Madrigal. If you’re like me you were saddened by the recent takedowns of the Google Flu Trend detection system. Data is supposed to help, right? In this article Alexis pushes past the naysayers as digs a bit deeper to find out why Flu Trends was built and how it was meant to be used. Hint – you still need people to help make sense of “big data.”

Making JSON as Simple as a Spreadsheet. I’ll be completely honest here. My programming skills end where JSON begins. Thankfully the Sunlight Foundation has developed a released a fantastic tool for people like me.

This Computer Can Tell When People Are Faking Pain by Greg Miller. First, a disclaimer. I used to work right next to the research group that developed this technology. Their research was always fun to learn about over quick coffee breaks or walks up the stairs in our building. Read this article with a bit of wonder and look for inspiration. If a computer with a camera can learn about pain and emotions how would you use it to learn about yourself?

Visualizations

Edward Tufte Wants You to See Better. This is a must read (or listen to) interview of Edward Tufte by Science Friday host, Flora Licthman.

I’m, at my best, on a kind of innocent and contrary posture, I think, wide-eyed, but somewhat skeptical posture.

My Personal Dashboard by Ahmet Al Balkan. I’m a big fan of self-made data dashboards. Especially when designers put them up on Githhub!

Everythign I Own by Thomas Stoller. This is just one in a series of self-tracking art projects by artist and student, Thomas Stoller. For this project Thomas took a photo of everything he owned and then resized the images to represent how much he actually uses them.

Vizual Statistix by Seth Kadish. This tumblr is an excellent source of inspirational visualizations.

Connected to the Self-Life and Re-Life by Luna Coppola. I’ve always been interested in how people use self-portraits as a form of self-tracking. This powerful photo project chronicles Luna’s experience with chronic kidney disease.

From the Forum

Raw heart rate data during sleep
Perpetual Life Hacker – Is it possible to hack Rock Climbing?
Dealing With People Privacy
Any Recommendations for Free Time Trackers

Posted in What We're Reading | Tagged | Leave a comment

QS Bay Area Meetup Recap

QSBA_Explo

On March 26th we hosted a fantastic Quantified Self Bay Area meetup at the new Exploratorium space overlooking the San Francisco bay. Over 180 people came together to mingle, learn about new self-tracking tools, and hear from our wonderful speakers.

Our thanks to the companies and organizations who demoed their tools: AddApp, Automatic, ExogenBio, Lumo Body Tech, Metro Mile, Ohmconnect, Reporter, uBiome, and UC Irvine.

We were lucky to have four great presenters talk about their personal self-tracking process. Philip Thomas spoke about building his personal dashboard. Maria Benet talked about how she used self-tracking to lose 50 pounds and take up sport she never dreamed of. Michael Cohn described his use of time tracking and personal commitment contracts. Lastly, Sky Christopherson gave us an update to his wonderful self-tracking talk from a few years ago and how that turned into helping the Women’s US Olympic Track Cycling Team bring home a silver at the London Olympics in 2012. Videos of these talks will be up soon!

Our special thanks go out to Colleen Proppé (who provided the beautiful photo above) and John Schrom who were both live-tweeting the meeting.

Posted in Meeting Recaps | Tagged , , | Leave a comment

The State of Self Tracking (QS London Survey)

The excellent organizers of the London Quantified Self Show&Tell recently fielded a detailed survey about the self-tracking practices in their group. In the video below Ulrich Atz presents their findings.

Some of the interesting results from the survey:

  • 105 respondents (22 identified as female, 76 as male).
  • Over 500 unique tools were being used.
  • 47% of the respondents are currently measuring weight (17% have in the past).
  • Pen & paper is being used by 28% of respondents.
  • 90% of respondents who answered a question about data sharing would share their data (or share it for medical research).

QSLondon_tracking2

The presentation is available online here (PDF) and an aggregate view of the survey results is also available for you to explore here. We’re excited to see and learn more from this interesting data set in the future.

Posted in Videos | Tagged , , , , , | Leave a comment

Thomas Christiansen on Learning from 60,000 Observations

It’s an iterative process. I’m peeling an onion, and I can continue peeling that onion for the probably the rest of my life.

How many times have you sneezed today? This month? Over the last 3 years? Thomas Christiansen knows his sneeze count because he’s been tracking them since 2011. We’ve actually heard from Thomas before, but we were happy to have him give an update on his unique self-tracking project at the 2013 Quantified Self Global Conference.

To better understand his allergies and his overall health, Thomas began tracking a discrete phenomena, his sneezes. By plotting them over time and then exposing himself to other data like sleep, travel, and diet he’s been able to start to understand himself better. Watch his talk below to see what Thomas learned, and how he thinks about his process of continuous learning.

This video is from our 2013 Global Conference, a unique gathering of toolmakers, users, inventors, and entrepreneurs. If you’d like see talks like this in person we invite you to join us in Amsterdam for our 2014 Quantified Self Europe Conference on May 10 and 11th.

Posted in Conference, Videos | Tagged , , , , , | Leave a comment