Tag Archives: qstop
“How can I define what makes me happy and what makes me sad, what is good for me?”
In 2012 Benjamin Bolland was finishing up his undergraduate degree and working on a new start-up. He found that his moods were constantly changing and wondered if there was something he could do to make sense of them as they moved “up and down.” He began tracking his mood with an simple self-designed Google Form. Each day at 11AM and 6PM he reported his mood on a 1-10 scale and wrote a quick descriptive note. After 1.5 years of doing this nearly every day he realized that he didn’t really know what was making him happy or sad so he decided to update his Google Form to include a variety of different categories that he thought might affect his mood including physical health, sport participation, and many others. In this talk, presented at the Berlin QS meetup group, Benjamin describes his process and how he’s used this mood tracking process to be more reflective and mindful during his daily life.
It’s commonly believed that we sleep away approximately a third of our lives. Is it good sleep? Does it help us refresh and regenerate? What can we do to make our time spent in bed even better?
Join us at our upcoming QS15 Global Conference and Exposition on March 13-15 in San Francisco to learn first-hand about how to track your sleep and benefit from your sleep data.
We’re excited to have our QS Washington DC meetup organizer, PhD student, and avid self-tracker, Daniel Gartenberg, sharing his deep knowledge of tracking sleep. Daniel has used multiple devices to find out what works and what helps him achieve a better night’s sleep, including the Sleep Smart Alarm Clock, Galaxy Gear watch, the Actiwatch (a research validated devices), and the Hexoskin shirt. We may even get a peek at the sleep tracking capacities of the Apple Watch.
Daniel’s Sleep Tracking 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. This year, QS15 is going to be two full days of self-tracking talks, demos, and in depth discussion, followed by a third day for a grand public exposition of the latest self-tracking tools. Join us at the Fort Mason Center on the San Francisco Waterfront. We’ve made some early bird tickets available for readers of the Quantified Self blog (for a limited time): Register here!
This week we have five meetups in four countries! The meetup in Warsaw will feature a show&tell on what can be learned from combining one’s genetic and microbiome data. The first QS group, Bay Area, will be having their meetup in Berkeley and will feature talks about running data and memorizing personal events.
After two very successful events, Vienna will be hosting their third show&tell. Copenhagen will feature a talk by Mette Dyhrberg, who once provided us with this excellent visualization. The Vancouver group is teaming up with a hardware-focused meetup for presentations on the world of personal data sensors.
To see when the next meetup in your area is, check the full list of the over 100 QS meetup groups in the right sidebar. Don’t see one near you? Why not start your own!
Monday (November 10)
Wednesday (November 12)
Friday (November 14)
Vancouver, British Columbia
We had a lot of fun putting together this week’s list. Enjoy!
A Spreadsheet Way of Knowledge by Steven Levy. A few weeks ago we noted that it was the 35th anniversary of the digital spreadsheet. Steven Levy noticed too and dug up this piece he wrote for Harpers in 1984. If you read nothing else today, read this. First, because we should know where our tools come from, their history and inventors. And second, but not last nor least, because it has wonderful quotes like this:
“The spreadsheet is a tool, and it is also a world view — reality by the numbers.”
The Ethics of Experimenting on Yourself by Amy Dockser Markus. With new companies cropping up to help individuals collect and share their personal data there has been an increased interest in citizen science. A short piece here at the Wall Street Journal lays the groundwork for what may become a contentious debate between the old vanguards of the scientific institution and the companies and citizens pushing the envelope. (The article is behind a paywall, but we’ve archived it here.)
Better All The Time by James Surowiecki. I started reading this thinking it would be another good piece about the digitization of sport performance and training, and it was, but only partly. What begins with sports turns into a fascinating look at how we are succeeding, and in some cases failing, to improve.
Article 29 Data Protection Working Party: Opinion 8/2014 on the Recent Developments on the Internet of Things. Do not let the obscure boring title fool you, this is an important document, especially if you’re interested in personal data, data privacy, and data protection rights. Most interesting to me was the summary of six challenges facing IoT data privacy and protection. I’m also left wondering if other countries may follow the precedents possibly set by this EU Working Party.
30 Little-Known Features of the Health and Fitness Apps You Use Every Day by Ash Read / AddApp. Our friends at AddApp.io put together a great list of neat things you may or may not know you can do with various health and fitness apps.
Man Uses Twitter to Augment his Damaged Memory by John Paul Tiltow. Wonderful piece here about Thomas Dixon, who uses Twitter to help document his life after suffering a traumatic brain injury that severely diminished his episodic memory. What makes it more interesting is that it’s not just a journal, but also a source of inspiration for personal data analysis:
”Sometimes if I have like an hour, I’ll be like ‘How’s the last week been?’“ Dixon says. ”I’ll look at the past week and I’ll go, ‘Oh, okay. I really do want to get a run in.’ So I will use it to influence certain decisions.”
Patients and Data – Changing roles and relationships by David Gilbert and Mark Doughty. Another nice article about the ever-changing landscape that is the patient/provide/insurer ecosystem.
The Quantified Anatomy of a Paper by Mohammed AlQuaraishi. Mohammed is a Systems Biology Fellow at Harvard Medical School, and he’s an avid self-tracker. In this post he lays out what he’s learned through tracking the life of a successful project, a journal publication (read it here), and how he’s applying what he learned to another project.
Calories In, Calories Out by (author unknown). A fascinating post about modeling weight reduction over time and testing to see if said model actually matches up with recorded weight. Not all math and formulas here though,
“I learned several interesting things from this experiment. I learned that it is really hard to accurately measure calories consumed, even if you are trying. (Look at the box and think about this the next time you pour a bowl of cereal, for example.) I learned that a chicken thigh loses over 40% of its weight from grilling. And I learned that, somewhat sadly, mathematical curiosity can be an even greater motivation than self-interest in personal health.”
Fitness Tracker on a Cat – Java’s Story by Pearce H. Delphin. A delightful post here about tracking and learning about a cat’s behavior by making it wear at Fitbit. Who said QS has to be serious all the time?!
100 Days of Quantified Self by Matt Yancey. Matt downloaded his Fitbit Flex data using our data export how-to then set out analyzing and visualizing the data. Make sure to click through for the full visualization.
IAMI by Ligoranoreese. If you’re in San Francisco consider stoping by the Catherine Clark Gallery for this interesting exhibit. The duo, Ligoranoreese, created woven fiber optic artwork based on Fitbit data.
From the Forum
Anyone have a good way to aggregate and visualize data?
Questions about personal health tracking
Call for Papers: special issue of JBHI on Sensor Informatics
Sleep Tracking Device – BodyEcho
On October 23rd, the QS Stockholm meetup group meetup collaborated with the Bionyfiken, a Swedish biohacking meetup, to host a meeting at the Karolinska Institute. We’re happy to share a recap from Mina Makar and Dina Titkova, a member and co-organizers of QS Stockholm .
The meetup was conducted in a very relaxed atmosphere starting with a small introduction by the organizers followed by a short video of Gary Wolf introducing Quantified Self. We then had a few presentations from our group members.
Tina Zhu is a PhD student at KTH with focusing on Biofeedback. She talked about her interesting project of visualizing self-tracking data in the form of a fish in an aquarium. It was very interesting to see such data representation being taken to another level which could be easier for some to accept, understand, and interact with. Learn more about her work here: http://bodyandnature.
Glenn Bilby is an experienced sport medicine specialist then took the audience on a journey of all the gadgets that he has been using over the last 20 years to keep track of his different activities. During his presentation, Glenn discussed different topics related to how to use the data generated from the different devices and concluded that there is still much to be done when it comes to adding more meaning to the data.
Fredrik Bränström and Tom Everitt started a very interesting platform using a new algorithm to visualize data and highlight links between variables. This method is designed to give users a different perspective on how their daily activities are associated to each other. Their platform is available for testing here: www.kaus.se.
Sina Amoor Pour presented his reflections on what biofeedback and biohacking are and background on the Bionyfiken group.
Chai demonstrated how different chips could be implemented into the human body in order to perform different activities. He spoke about the wide range of applications for such chips ranging from starting your own car or bike.
If you’re based in Sweden, don’t miss the upcoming QS Stockholm meetups for more inspiration and ideas.
“There was nothing in my life pushing me to to have these more intimate relationships, the few people I actually care about.”
When Akshay Patil was putting together the guest list for his wedding he realized that it had been a long time since he’d spoken with some of the the people he was inviting. Even with his good friends, he surprised by his lack of communication, his inability to stay connected. As anyone faced with this realization he decided to try and change, but the realities of life quickly crept back and as they say, old habits die hard. When he left his last job and began looking for projects to work on, this troubling area of his life crept back to the fore. Maybe there was something he could do better track and change his communication and relationships. Using his development skills, and the ability to gather data from his Android phone, he decided to build a system that helped him stay in touch with the people that mattered most to him. In this talk, presented at the New York QS meetup group, Akshay talks about what’s he’s learned from using this app, including when it fails.
Siva Raj was interested in lowering his blood pressure. With a family history of cardiovascular disease and heart attacks he was worried about slightly elevated blood pressure (pre-hypertension). As someone engaged with understanding and building fitness applications he thought he would be able to lower his blood pressure by staying on track with a regular exercise program that focused on cycling. Interestingly his blood pressure measurement didn’t respond to his constant exercise or weight loss. After reading more research literature about the link between fitness and cardiovascular health Siva decided to change his training to improve his fitness. He decided to incorporate a increased intensity into his routine. After a short period of time he had increases in this fitness and was able to observe the reduction in blood pressure he was looking for. In the video below, filmed at the Boston QS meetup group, Siva explains his methods and talks about how he was able to track his body’s response to different fitness routines.
There will be two Quantified Self meetups this week, both of which will be in the United States. I’m looking forward to seeing the Show&Tell videos that come out of these!
To see when the next meetup in your area is, check the full list of the over 100 QS meetup groups in the right sidebar. Don’t see one near you? Why not start your own!
Wednesday (November 5)
Saturday (November 8)
Dallas/Fort Worth, Texas
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.”
Jamie Williams found himself with almost two years of self-tracking data including physical activity, blood pressure, and weight. Because of his interest in data visualization and coding he decided to learn how to access it the data and work on visualizing and understanding some of the trends and patterns. In this talk, presented at the QS St. Louis meetup group, he takes a deep dive into his activity and step data as well as his blood pressure data to learn about himself and what affects his behavior and associated data.
What Did Jamie Do?
Out of pure interest in seeing what the data would reveal, Jamie utilized a combination of devices to track his physical activity, blood pressure, heart rate, weight, numbers of drinks, and automobile travel. He then went on to explore ways in which he could pull down, integrate, visualize, and ultimately make sense of what he collected.
How Did He Do It?
In order to obtain his data on a minute-level resolution, Jamie had to email FitBit for a specialized use of their API. He then employed Mathematica to develop a number of (beautiful) visualizations of his activity – along with other key moments in his life (moving to St. Louis, changing job location, preparing for a Half Marathon, etc.). Jamie was able to compare his data not only to his peers through FitBit, but also to others of his demographic in the U.S. using the publicily available NHANES data set.
What Did He Learn?
Through Jamie’s Quantified Self collection and analysis efforts, he learned a lot not only about the patterns and changes in his activity, but why they were the case. He also presented great feedback about one’s mindset when comparing to peers vs. the general population.
Withing Blood Pressure Cuff
Thank you to QS St. Louis organizer, William Dahl, and Jamie for the original posting of this talk!