Tag Archives: weight
On June 18-20 we’ll be hosting the QS15 Conference & Expo in San Francisco at the beautiful facilities at the Fort Mason Center. This will be a very special year with three days of inspiring talks, demos, and discussion with your fellow self-trackers and toolmakers. As we start to fill out our program we’ll be highlighting speakers, discussion leaders, sponsors, and attendees here.
Julie Price is a long time member of our Bay Area QS meetup group and will be attending the QS15 Conference & Activate Expo to share her self-tracking story. Julie has been using and experimenting with a wide range of self-tracking tools and behavioral techniques to understand herself. Previously she’s shared her experiences using commercial tools and self-designed methods to understand and improve her marathon training.
Over the past 4 years, Julie has tracked her weight as it moved within a 30 pound range, varying wildly within each year. In December, Julie shared the factors that influenced her weight the most: family visits, distance road races, and a variety of weight loss tactics. As part of our show&tell program, Julie will share an update that includes her newest insights into her weight fluctuations as well as what interventions have made the greatest impact on her weight.
We’re excited to have Julie joining us and asked her a few questions about herself and what she’s looking forward to at the conference.
QS: What is your favorite self-tracking tool (device, service, app, etc)?
Julie: Hands-down, I love the Whistle to measure my dog’s activity. I use Basis Peak and my husband uses Jawbone Up. Both seem well-designed for certain scenarios and not for others. Between all the wearables we’ve tried, the Whistle has been the most successful in influencing our behavior.
QS: What are you most looking forward to at the conference?
Julie: I’m looking forward to meeting interesting people, learning from their stories, and learning from their creative experiments and observations. But, I’m most looking forward to exploring new ideas that impact the behavior of people who don’t necessarily enjoy data.
QS: What should people come talk to you about at the conference?
Julie: I’m an expert in UX, interaction design, usability, health behavior change, and fitness. I’d love to talk about creative tactics for eliciting behavior change and a process for ensuring the right product and experience is designed for the right person. I also love to talk about health gaming and the complexities of the space.
QS: What tools, devices, or apps do you want to see at the conference?
Julie: Any product in health and fitness that is truly different or thought through from the perspective of the user. I’d love to see any product built with a process that continually validates their direction with target users.
QS: What topic do you think that Quantified Self community is not talking enough about?
Julie: We should explore more innovative ways to meet people where they are and creatively influence them gradually in a way that is meaningful and lasting. It would be great to talk more about what progressive techniques could be applied in order to create impact over both short and long periods of time.
Julie’s session is just one of the many hands-on, up-to-date, expertly moderated sessions we’re planning for the QS15 Global Conference and Exposition. Register here!
Julie Price has been tracking her weight consistently for the last four years. Like many of us, she found that her weight goes up and down depending on various life events. In this talk, presented at the Bay Area QS meetup group, Julie discussed what she’s learned about her weight and what correlates with weight gain and weight loss. Specifically, she focuses on the role of family gatherings, exercise and running races, and how different food and dieting methods either helped of hindered her progress.
We’re excited to have Julie joining us at our 2015 QS Global Conference and Exposition on June 18-20th. Early bird tickets are now available, and we hope you can join us for a great three days of learning, sharing, and experiencing the latest in QS techniques and tools. Register now.
David Joerg is a software developer in New York City and had some interest in personal data. Inspired by attending his first QS meetup in late 2013, he decided to take a deeper dive into the data he was collecting, add some new systems, and see if he could build something to help him better understand himself. What he ended up building was his own data dashboard, a personal operating system, that allowed him to see how he was doing across the various metrics he was interested in including, sleep, exercise, weight, unread emails, and more. In this talk, presented at the New York QS meetup group, David explains his process and what he learned from developing and using this system.
“When I look at this, this is the story of my life in these years.”
Nan Shellabarger has been tracking her weight for 26 years, including almost daily tracking since 1998. In the talk embedded below, presented at the Washington DC QS meetup group, Nan describes her experience with diving deep into how she’s making sense of her weight data. By looking over her complete history and layering in her personal contextual data she was able to find how different life events played a role in weight loss and gain. For example, she found that physical challenges and events were “tremendous motivation to get out there and doing things as well as helping me focusing on my eating.” Nan has also used a variety of activity trackers since 2010, starting with the Body Media Fit and now the Garmin Vivofit and Jawbone UP. These devices helped her explore calorie expenditure as it relates to her weight loss. On the other side of the equation, she also explored how diet tracking influenced her weight. Watch her great talk below to hear the whole story.
We hope to see an update of this great talk when Nan joins us at our QS15 Global Conference and Exposition next June in San Francisco. Early bird tickets are available for a limited time. Register now!
We’re back after missing last week (sorry!) with a bit longer list than usual. Enjoy!
Thoughts on Quantified Self for Modifying Long Term Life Goals by Mark Krynsky. Mark, a member of our QS Los Angeles meetup group, is consistently putting together interesting ideas in the QS space. In this short post he explore how QS tools might be used to understand long-term life goals.
Open Data for Open Lands by Alyssa Ravasio. The value of data isn’t confined to what we can understand about ourselves. There is so much beneficial information out there, especially when it comes to public data. In this post, Alyssa makes the case for protecting and promoting open data ideas and concepts regarding out most precious public spaces – the national parks system.
Art at the Edge of Tomorrow: Lillian Schwartz at Bell Labs by Jer Thorpe. A wonderful biographical piece about Lillian Schwartz, a pioneer in the field of computational art and exploration.
Terms of Service by Michael Kelller and Josh Neufeld. A reporter and nonfiction cartoonist team up to use a comic to tell us about the new world of data and privacy we currently inhabit. Interesting format and compelling content!
Narrative Camera by Morris Villarroel. Morris has been wearing a Narrative personal camera for six months. In this short post he explains what he’s learned and experienced over that time.
Where my 90 Hours of Mobile Screen Time in September Went by Bob Stanke. Bob used an app (Trackify) on his Android phone to track how much time he was spending on his phone and what apps he used the most.
Quitting Caffeine by Andrei-Adnan Ismail. Andrei wasn’t happy with his relationship with coffee and caffeine so he he decide to try and quit. Using tracking and really interesting use of “sprints” to gradually reduce his consumption, Andrei was able to quit. Great post here describing his process and the data he gathered along the way (including how his change affected his sleep).
Twitter Pop-up Analytics by Myles Harrison. Myles takes us through the process of downloading, visualizing, and analyzing personal data from Twitter.
Seven Months of Sleep by Eric Boam. A bit of an old one here, but beautiful and informative nonetheless. Make sure to read the accompanying piece by Eric. (I’m also looking forward to seeing more about this dataviz of his Reporter app data soon.)
My latest effort to visualize my calorie intake and weight loss by reddit user bozackDK. Using data collected from MyFitness pal, bozackDK has created this great visualization of his data. I asked what was learned from making this graph and received this wonderful response:
“I make graphs like these to keep myself going. I need some kind of proof that I’m doing alright, in order to keep myself wanting to go on – and a graph showing that I can (somewhat) stay within my set limits, and at the same time showing that it actually works on my weight, is just perfect.”
Shawn Dimantha is always looking for easier ways to track his health. He uses a variety of self-tracking tools, but a few months ago he became interested in exploring what he could do given his engineering and health IT background. He was inspired by immersion, an MIT-developed email analysis tool, which helped him understand who he was communicating with, and by Wolfram Alpha’s Facebook analysis tool. Focusing on Facebook and the wealth of image-based data in his profile he asked himself if images could be a window into his health. After reading a research paper on the use of images to predict body mass index he decided to see what he could learn my implementing a similar procedure on his own images.
What Did Shawn Do?
I used photos from my Facebook account to track my health, the reason I did this because I wanted to see how a simple heuristic I used for tracking my health daily could be implemented in the online world given the huge amount of photos that are and have been shared on a daily basis. I notice when I gain or lose weight, am stressed or relaxed from my seeing my face in my mirror. I was partly inspired by the self-photo collages presented on YouTube.
How Did He Do it?
I selected photos of my face from my Facebook account, cropped out my face and used some software and manual tagging to measure the ratio of different fiducial points on my face (eye-eye length, and cheek to cheek length) over time to help serve as a proxy for my health.
What Did He Learn
Facial image data needs to be cleaned and carefully selected. Face shapes are unique and need to be treated as such. Data that is not present is often more telling than what is present. Life events effect my weight and should be put into context; however causation is harder to determine than correlation. By being more conscious of my score and I can change my behavior before things get off track.
Right now I’m turning this into a product at Enfluence.io where I’m focused on using it to help with preventive health.
Facebook (my own images)
Python / OpenCV
Slides from Shawn’s talk are available here.
We hope you enjoy this week’s list!
Big Data in the 1800s in surgical science: A social history of early large data set development in urologic surgery in Paris and Glasgow by Dennis J Mazur. An amazing and profoundly interesting research paper tracing the use of “large numbers” in medical science. Who knew that is all began with bladder stones!
Civil Rights, Big Data, and our Algorithmic Future by Aaron Rieke, David Robinson and Harlan Yu. A very thorough and thoughtful report on the role of data in civil and social rights issues. The report focuses on four areas: Financial Inclusion, Jobs, Criminal Justice, and Government Data Collection and Use.
Caution in the Age of the Quantified Self by J. Travis Smith. If you’ve been following the story of self-tracking, data privacy, and data sharing this article won’t be all that surprising. Still, I can’t help but read with fascination the reiteration of tracking fears, primarily a fear of higher insurance premiums.
Patient Access And Control: The Future Of Chronic Disease Management? by Dr. Kaveh Safavi. This article is focused on providing and improving access and control of medical records for patients, but it’s only a small mental leap to take the arguments here and apply them all our personal data. (Editors note: If you haven’t already, we invite you to take some time and read our report: Access Matters.)
Perspectives of Patients with Type 1 or Insulin-Treated Type 2 Diabetes on Self-Monitoring of Blood Glucose: A Qualitative Study by Johanna Hortensius, Marijke Kars, and Willem Wierenga, et al. Whether or not you have experience with diabetes you should spend some time reading about first hand experiences with self-monitoring. Enlightening and powerful insights within.
Building a Sleep Tracker for Your Dog Using Tessel and Twilio by Ricky Robinett. Okay, maybe not strictly a show&tell here, but this was too fun not to share. Please, if you try this report back to us!
Digging Into my Diet and Fitness Data with JMP by Shannon Conners, PhD. Shannon is a software development manager at JMP, a statical software company. In this post she describes her struggle with her weight and her experience with using a BodyMedia Fit to track her activity and diet for four years. Make sure to take some time to check out her amazing poster linked below!
The following two visualizations are part of Shannon Conners’ excellent poster detailing her analysis of data derived from almost four years of tracking (December 2010 through July 2014). The poster is just excellent and these two visualizations do not do it justice. Take some time to explore it in detail!
Tracking Energy use at home by reddit user mackstann.
“The colors on the calendar represent the weather, and the circles represent how much power was used that day. The three upper charts are real-time power usage charts, over three different time spans. I use a Raspberry Pi and an infrared sensor that is taped onto my electric meter. The code is on github but it’s not quite up to date (I work on it in bits and pieces as time permits I have kids).”
Like anyone who has ever been bombarded with magazine headlines in a grocery store checkout line, Kouris Kalligas had a few assumptions about how to reduce his weight and improve his sleep. Instead of taking someone’s word for it, he looked to his own data to see if these assumptions were true. After building up months of data from his wireless scale, diet tracking application, activity tracking devices, and sleep app he spent time inputing that data into Excel to find out if there were any significant correlations. What he found out was surprising and eye-opening.
This video is a great example of our user-driven program at our Quantified Self Conferences. If you’re interest in tell your own self-tracking story, or want to hear real examples of how people use data in their lives we invite you to register for the QS15 Conference & Exposition.
On July 4th, 2009 Jan Szelagiewicz decided to make a change in his life. After taking stock of his personal health and his family history with heart disease he began a weight-loss journey that included a variety of self-tracking tools. Over the course of a few years Jan tracked his diet, activities such as cycling, swimming, and running, and his strength. In this talk, presented at the Quantified Self Warsaw meetup group, Jan describes how he used self-tracking to mark his progress and stay on course.
When we decide to track one thing, we sometimes find that we are indirectly tracking something else. That is the theme of today’s talk.
When Mark Leavitt was 57, he found out that he had heart disease, a condition that runs in his family. Mark set about making some life changes. He tracked his weight while adopting a low-fat diet. His tracking showed him that he was making progress and that progress encouraged him to keep tracking. But once Mark’s weight loss stalled and then started to backslide (though he had maintained his diet) his desire to track dwindled and was then snuffed out by a major life event.
Though he was ostensibly tracking weight, this experience gave him some insight into his motivation. He began to build a mental model of his willpower. When was it strong? When was it weak? Using his background as a doctor to make assumptions on the nature of his willpower, he used the tracking of other lifestyle changes, such as movement and strength-training, to test those assumptions and better understand how to follow through on his intentions.
Watch below to see what Mark found worked for him and if you would like to see how Mark’s keeping up with his habits, you can check out his live dashboard here.