Search Results for: weight
Last June, the Pew Internet Research Project released a report entitled, Family Caregivers are Wired for Health. The authors - Susannah Fox, Maeve Duggan and Kristen Purcell - found that 40% of Americans are caring for an adult or child with significant health issues. Of special interest to us: “When controlling for age, income, education, ethnicity, and good overall health, caregivers are more likely than other adults to… track their own weight, diet, exercise routine, or other health indicator.” (Emphasis added.)
Our Bay Area co-organizer Rajiv Mehta was a community peer reviewer of the survey. At the upcoming 2014 Quantified Self Europe Conference, Rajiv will co-lead a breakout with Dawn Nafus of Intel Labs on the role of families in self-tracking practice. If you are involved in or curious about family caregiving, you’re invited to come and take part in what will be a great discussion.
The QS Europe Conference is just a few weeks away; come if you can!
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.
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.
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.
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.
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?
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
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).
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.
Mark Drangsholt has been dealing with an issue with his heart since he was a young man. Since his early twenties, when he as diagnosed with paroxysmal atrial tachycardia he’s had to deal with irregular heart rhythms. In this talk Mark explains how the transition into adulthood negatively impacted his health and then how he used self-tracking and a focused athletic program to help him reduce his weight and improve his health. Most show&tell talks would end there, but Mark still had the irregular rhythm issue to deal with. After what he describes as an episode that made him think, “This is it. I’m going to die.” he decided it was time to apply his self-tracking process in order to understand his heart rhythm disorder and possible triggers. Mark also decided to go one step further and apply the principles of case-crossover design to his tracking methodology. Watch his talk below and keep reading to learn a bit more about why you might want to consider using case-crossover design in your self-tracking projects and experiments.
The following excerpt from the QS Primer: Case-Crossover Design by Gary Wolf provides a great background for his method:
Mark’s self-tracking data didn’t naturally fit with any of these approaches. To understand whether these triggers actually had an effect on his arrhythmias, he used a special technique originally proposed by the epidemiologists Murray Mittleman and K. Malcolm Maclure. A case-crossover design is a scientific way to answer the question: “Was the patient doing anything unusual just before the onset of the disease?” It is a design that compares the exposure to a certain agent during the interval when the event does not occur to the exposure during the interval when the event occurs.
Using this method, Mark discovered that events linked to his attacks included high intensity exercise, afternoon caffeine, public speaking to large groups, and inadequate sleep on the previous night. While these were not surprising discoveries, it was interesting to him to be able to rigorously analyze them, and see his intuition supported by evidence. “A citizen scientist isn’t even on the conventional evidence pyramid,” Mark notes. “But you can structure a single subject design to raise the level of evidence and it will be more convincing.”
Science. Someone makes an observation, creates a hypothesis, tests it, then analyzes the results against the hypothesis. Hopefully once a conclusion is reached it is tested again and again for validity and reproducibility. With self-tracking, the world of personal science and experimentation is opening up real-world personal laboratories to test the findings, claims, and promises available through the popular and scientific literature.
Nick Alexander is one of these self-experimenters. When he started to hear about thermodynamics and the effect of temperature on exercise and energy expenditure he decided to set up his own experiment:
I had been introduced to thermodynamics exercise research by former NASA scientistRay Cronise via Wired and the Four Hour Body. Ray makes an extraordinary claim (i.e. that exercising in a cold environment, especially in cold water, causes a large increase in calorie burn), and I was curious to see if it would work for me.
In this talk, given at the 2013 Quantified Self Global Conference, Nick explains his experimental setup and what he found after tracking over 30 runs and crunching the numbers. For a more in-depth discussion about his methodology and his findings I recommend reading his recaps.
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.
At Quantified Self Labs, we create and host events that bring together our community of trackers, toolmakers, researchers, and other individuals interested in how self-tracking is shaping our culture. We focus mainly on meetups and conferences. With the 2014 Quantified Self Europe Conference coming up in May, we thought we’d let you know what makes it a unique and rewarding experience for us and our growing community.
When and Where
Since our first European Conference in 2011, we’ve been lucky to present at the Casa 400 Hotel in beautiful Amsterdam. This year’s conference will take place on May 10th and 11th to take advantage of the spring weather. Casa 400 is just a short bike ride from central Amsterdam and is conveniently located within waking distance of a public train station.
Our conferences are unique community-driven events that we like to refer to as “carefully curated unconferences”. All of our sessions and talks come from our conference attendees, which requires more hands-on work from our program staff. The end result is dynamic program that reflects the interest, insights, and experiences of our community. Our program is divided into four different types of sessions and presentations held concurrently throughout both days of the conference.
Show & Tell Talks: These talks are personal first-person self-tracking stories. We ask speakers to present their tracking experiments with an emphasis on what they’ve learned. At previous conferences we’ve heard talks on tracking Parkinson’s disease, computer use, continuous heart rate, and other fascinating subjects.
Breakout Discussions: Held concurrently with Show & Tell talks, the breakouts are group discussions about a specific topic related to Quantified Self. Each discussion topic is proposed and led by a conference attendee. Previous breakouts have touched on issues related to privacy, the “missing trackers”, DIY tracking, visualization design, the role of open data in the QS community, and many others.
Lunchtime Ignite Talks: After a healthy and delicious meal (lunch is provided) we encourage attendees to listen to six or eight rapid-fire Ignite talks from other participants. These talks are similar to our Show & Tell talks, but are typically more light-weight and entertaining. A great example is this talk given by Mark Moschel on tracking rejection.
Office Hours: We encourage participants to bring current projects, tools, or applications they’re working on. We provide office hour space during program sessions for people to present their project and interact with attendees in one-on-one conversations. We’ve been delighted to see a wide range of concepts exposed during office hours such as art projects, new visualization methods, meet and greets with luminaries in the field, and new tool prototypes.
Take a peak at our 2012 European Conference program for more examples of how we put together a collaborative program packed with learning and sharing opportunities.
Sponsors and Friends
We couldn’t create our conferences without the support of our generous sponsors. We’d like to thank our current annual sponsors, Autodesk and Intel, for their continued support. We are grateful for the support from this year’s conference sponsors: Gero Lab, Aro (Saga), Scanadu, Withings, and Zensorium. If you’re interested in sponsoring our work in general, or the upcoming European Conference, please get in touch.
We also want to thank our Friends of QS. These toolmakers, inventors, and entrepreneurs directly support our work and community. If you’d like to learn more about our Friends of QS program just let us know.
If you are an advanced user, designer, inventor, entrepreneur, journalist, scientist, or health professional, please join us in beautiful Amsterdam for two days of collaboration and inspiration!
We expect to sell out, so if you plan to attend please register today!
Enjoy the information, ideas, and other bits of interestingness we’ve found compelling this week.
Articles and Posts
Medicine gets up close and personal by W. Wyatt Gibbs. At Quantified Self Labs we are big fans of Leroy Hood and his work at the Seattle based Institute for Systems Biology. In an effort to better understand longitudinal health he is spearheading a new pilot research project to track 100 people (genome, sleep, activity, etc.) and eventually hopes to enroll 100,000 people and follow them for 25 years. You can learn more about Dr. Hood’s ideas and this research in this short video.
The Couple That Pays Each Other to Put Kids to Bed by Ben Popken. It is not often that we get to peek into the lives of our Quantified Self community members. In this profile we learn how Bethany Soule and Daniel Reeves use game theory and behavioral economics to divvy up daily tasks in their household. You may also know Daniel and Bethany as the great team behind one of our Friends of QS, Beeminder.
How Science Turned a Struggling Pro Skier Into an Olympic Medal Contender by Jeffrey Marlow. With the 2014 Winter Olympics in full swing we’ve started seeing a number of articles detailing the role technology and self-tracking has played during the lead up to competition. This piece is a great look into the different methods the US Ski Team is using to gain and edge on their competition.
The pedagogy of disgust: the ethical, moral and political implications of using disgust in public health [PDF] by Deborah Lupton. For decades many public health campaigns have used emotional imagery in an attempt to reduce negative health behaviors. This research article, by one of our favorite sociologists, explores the history of using disgust in public health campaigns and the implications this practice has on different communities.
How Can We Help People Get More Sleep? by Lori Melchar. Lori is a program director at the Robert Wood Johnson Foundation and recently took part in a panel discussion on sleep. Due to the foundation’s involvement in numerous health research projects Lori was able to provide some insight into the current challenges and possible solutions for combating sleep loss.
The Weight of the Rain by Jonathan Corum. Jonathan is a senior graphics editor at the New York Times and he gave a talk at the recent Visualized Conference in New York. It’s by far one of my favorite pieces on designing and creating data visualizations that I’ve read this year.
Baseline Cherrypicker by Ben Schmidt. If you’re interested in data visualization and have a soft spot for baseball statistics you can’t do better than this great tool. (The Yankees are clearly the most dominate team in history.)
Where People Run by Nathan Yau. I’m a big fan of Nathan’s work over at Flowing Data. In this post he uses publicly available data from Runkeeper to plot routes for 22 major cities around the world. Apparently people love running near bodies of water.
Ranking Data Dashboards on Pinterest by Mike McDearmon. Mike is a member of the QS New York meetup group and he’s been actively keeping examples of data dashboards on Pinterest. In this short post he examines the number of re-pins to see what dashboards are most popular.
From the Forum
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