Tag Archives: weight
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.
Katrina Rodzon thought she was a relatively healthy person until she realized that seemingly disconnected symptoms pointed towards something real, a gluten intolerance. She took this hunch and decided to test it out using a simple elimination diet along with tracking her weight and subjective bloating and mood ratings. Watch her great talk from our 2013 Global Conference to find out what she learned.
Even in a world of connected devices, wearable technology, and near ubiquitous data connections self-tracking and personal data collection can be difficult endeavor. Aaron Parecki has been tracking various aspects of this life for years – specifically location, weight, and sleep. We’ve covered some of Aaron’s work and his amazing geolocation visualizations here before and we were excited to have him speaking about his experiences at our 2013 Global Conference. Watch this fantastic talk to hear about Aaron’s tracking practices and his thoughts on why a personal data server is an important tool.
Update: Aaron let us know that his slides from this talk are also available and can be viewed here.
We’ll be posting videos from our 2013 Global Conference during the next few months. 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.
I gained a lot of insights from this heat map. The most obvious weight gain was no surprise — that’s when I periodically don’t track. In any case, the big picture patterns are easily identified with a heat map.
Realized looking at this heat map that the point of no return was mid-April 2012 — my data shows that was when I switched protein shakes with an egg based breakfast. I have since experimented and seen that protein shake in the morning seems to keep my blood sugar more stable and as a result my weight under control!
We invite you to take part in this project as we share our favorite personal data visualizations.If you’ve learned something that you are willing to share from seeing your own data in a chart or a graph, please send it along.
There is nothing quite like having to unexpectedly deal with your own mortality. Mark Leavitt experienced that “wake up call” when he spent Thanksgiving in 2007 at a cardiac cath lab. While he didn’t have a heart attack, he left with 3 stints and new outlook. He decided to take a hard look at his “comfortable life” and see what he could change. After a successful diet and exercise regimen helped him lost 35 pounds he found himself slowly re-gaining weight. What happened next was amazing. Watch this great talk and Q&A to learn how he tracked and hacked his computer time to make it a much healthier endeavor.
This talk was filmed at our 2012 Quantified Self Global Conference. We hope that you’ll join us this year for our 2013 Conference where we’ll have great talks, sessions, and discussions that cover the wide range of Quantified Self topics. Registration is now open so make sure to get your ticket today!
Jae Osenbach LOVES chocolate. Unfortunately, her body does too. She decided to go on a calorie-restricted diet of 1200 calories a day for 6 weeks and track her weight loss. In the lively video below, Jae talks about her experiments with nuts vs. no nuts and chocolate vs. no chocolate, and her surprising T-test results. She has also kindly posted her slides and instructions for how to add an analysis toolpak to Excel. Hooray for chocolate! (Filmed by the Seattle QS Show&Tell meetup group.)