Tag Archives: running
Philosophy, bicycles and brains, opinions on tracking sleep, learning from actually tracking sleep, and visualizing work through vigilant self-report – all these and more in our reading list below. Enjoy!
Sleep apps and the quantified self: blessing or curse? by Jan Van den Bulck. Here at QS Labs, we’re very interested in how the academic and research world is colliding with those of us using tools of measurement previously restricted to science. In this Letter to the Editor, published in the Journal of Sleep Research, the author lays out an interesting set of opinions about the increasing availability and use of commercial sleep tracking devices. (You can access the full pdf here.)
Measuring Brainwaves to Make a New Kind of Bike Map for NYC by Alex Davies. Readers of the QS website may remember a great show&tell talk we featured back in May of 2014. In that talk, Arlene Ducao discussed her MindRider Project, an EEG tracking bicycle helmet. In this short piece, we learn that Arlene has continued this awesome work and has produced MindRider Maps Manhattan, exposing the brain data of 10 cyclists as they transversed New York City.
Big Data and Human Rights, a New and Sometimes Awkward Relationship by Kathy Wren. Earlier this year the AAAS Science and Human Rights Coalition held a meeting to discuss the intersection of personal data collection and human rights. This short article describing some of the key discussion points is a great place to start if you’re exploring what “big” and personal data means to you and your use of the tools and services that collect it. (Videos of the meeting are also available.)
How Theory Matters: Benjamin, Foucault, and Quantified Self—Oh My! by Jamie Sherman. A very interesting and thought-provoking essay here on the nature of self-tracking and data collection framed against the works of Michel Foucault and Walter Benjamin. We count ourselves lucky to have Jamie as an active member and observer of our QS community.
But taken together, Foucault and Benjamin suggest that the penetration of data into daily life is part of a larger shift underway, and that changes we can already see in social life, politics, and labor are not unrelated, but rather intimately linked.
Compulsory Quantified Self by Gwyneth Olwyn. I think it’s good practice to try and expose ourselves to all sides of the conversation around self-tracking, the positive and the negative. In this blog post Gwyneth describes a few ideas about the purpose and outcomes of self-tracking, especially when the self is superseded by the demands of others (such as in a workplace wellness program).
Sleep Data Analysis with R by Ryan Quan. Ryan has been tracking his sleep with the Sleep Cycle app for the last two years. In this excellent post he explores and plots his data (yay export!) to see when he goes to sleep, how long he sleeps, and what really makes up “quality sleep.” Love the fact that he included his R code and sample data. Go Ryan!
Quantifying Goals Using Key Performance Indicators (KPIs) by Bob Troia. No data in this post, but I found it particularly inspiring to see how Bob was planning on keeping track of his goals for this year. If you’re looking for ideas for tracking your 2015 goals and Key Performance Indicators this is a great place to start.
The Resume Of The Future by Eric Boam. The above is one of the two beautiful visualizations created by Eric to explore his daily work activity and interactions. This visualization shows what he was actually spending his time on. How did he collect the data? Well, he used the Reporter App to ask himself three questions: “where are you, what are you doing, and who are you with?” Make sure to read his post, he developed very interesting insights through collecting this data.
Weight Loss: What Really Works? by Emi Nomura and Laura Borel. Another fascinating data analysis project here by the Jawbone data science team. They examined the behaviors of a group of users who lost at least 10% of their starting weight vs users with no weight loss and found that the biggest difference in behavior was tracking meals.
Mapping my Last Two Years of Runs and Rides
While browsing the r/dataisbeautiful subreddit I stumbled upon this interesting tool/company that visualizes the maps of your runs and bike rides by connecting to your Runkeeper or Strava account. Above I’ve included my 2013 and 2014 maps. Clearly I need to find some new running routes in my neighborhood. (click through to enlarge)
QS Access Links
As part of our new work highlighting stories, issues, and innovations related to personal data access we’re going to start publishing a short collections links in this space. As this works grows be on the lookout for a new Access Newsletter from QS Labs.
Who Should Have Access to Your DNA?
What FDA developments in Diabetes mean for FDA approval in Digital Health
Open consent, biobanking and data protection law: can open consent be ‘informed’ under the forthcoming data protection regulation?
WTF! It Should Not Be Illegal to Hack Your Own Car’s Computer
Unique in the shopping mall: On the reidentifiability of credit card metadata
Majority of Consumers Want to Own the Personal Data Collected from their Smart Devices
Who Owns Patient Data
Los Angeles County Supervisors OK Creation of Open-Data Website
We’ve put together an extra-long list for our last What We’re Reading of 2014. Enjoy!
Medical Inhalers To Track Where You Are When You Puff by Alison Bruzek. We’ve been following Propeller Health (nee Asthmapolis) for quite a while and this piece does a good job outlining their technology and promise.
How Self-Tracking Apps Exclude Women by Rose Eveleth. A great article on the issues brought on by the gendered design of self-tracking tools and applications. Good to see thoughts and experiences from some of our QS community members included in the piece. (If you’re a woman interested in women’s only QS meetups there are groups in New York, Boston, and San Francisco.)
The Echoes of Hearts Long Silenced by Ron Cowen. Humans have been curious about the sounds our bodies make for centuries. What could we learn from tracking and recording those curious buh-bumps? Sprinkled throughout this great article are examples of the the power of hearing and recoding the human heart.
The Genetic Self by Nathaniel Comfort. A great longer read on the ever expanding role personal genetics can have on our life, especially our health.
This brave new world need only be dystopian if we surrender our agency. If we are aware of the exchanges we are making and how our information is valued—if we are alert to the commodification of personal data—we can remain active players instead of becoming pawns.
More Data, Fewer Questions by Jer Thorp. “Every headline about data from the NYTimes containing a question, from 2004–2014.” (Part of an outstanding collection of predictions for the future of journalism in 2015] curated by the Nieman Lab.)
Dada Data and the Internet of Paternalistic Things by Sara M. Watson. A great piece of speculative fiction here that “explores a possible data-driven future.”
Tech Giants Move to Protect Wearables by Ashley Gold. With more wearables and QS tools capturing personal health data there is increasing scrutiny on privacy and protection, especially at the federal level.
Make Your Own Activity Tracker by Young-Bae Suh. Want to track your activity, but also love DIY projects? This is the one for you. A great walk through, including sample code, to get you up and running with a wrist-based activity tracker.
Enviro-Trackers Are a New Gadget Trend. What Do We Do With Them? by Margaret Rhodes. What can we do with personal environmental data? Margaret explores this question in the wake of the new devices currently available and being developed to track the world around you.
Vicious Cycle by Patt Virasathienpornkul. A fun student project that imagines a close-loop system of calorie consumption and expenditure.
Music Records by Salem Al-Mansoori. A wonderful deep dive into eight years of music listening history. Salem supplements the raw listening data with additional information and creates an amazing set of visualizations to answer questions such as, “Where do the artists I listen to come from?” and “How are my tastes changing over time.”
Half a Year with Dash by Colin Sullender. When the Dash OBD tracking device connected with the IFTTT service in mid 2014 Colin began logging each of this car trips. In this post he gets into the data to see what he can learn from his driving data.
Superpowering Runkeeper’s 1.5 Million Walks, Runs, and Bike Rides by Garrett Miller. The folks at Mapbox have done it again by improving on their last map collaborations with Runkeeper. Make sure to poke around in the large map to see where people are running, riding, and walking in your area. Also see this interview/article if you’d like to learn a bit more about the project.
A Year in Moves Data by Patrick Maloney. Patrick graphed his tie spent at time and at work by access his Moves data.
Crowdsourcing a Runkeeper Dashboard by Patrick Tehubijuluw. Patrick built a nice overview data dashboard to explore his Runkeeper data. If you’re a QlikView User you can download and play with your own data.
Tell, Don’t Show by John Pavlus. Data dashboards are all the rage in our mobile-focused personal data world, but do they do a good job conveying information? John Pavlus argues that “data verbalization” is the next big user experience.
From the Forum
Understanding Goal Setting and Sharing Practices Among Self-Trackers
Wearable Timelapse Camera? (For time management)
New book about Quantified Self, called Trackers
Determine your Fitbit stride length using a GPS watch
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.
Enjoy this week’s list!
Effect of Self-monitoring and Medication Self-titration on Systolic Blood Pressure in Hypertensive Patients at High Risk of Cardiovascular Disease by Richard McManus et al. An interesting research paper here about using self-monitoring to reduce blood pressure. The paper is behind a paywall, but since you’re nice we’ve put a copy here.
Apple Prohibits HealthKit App Developers From Selling Health Data by Mark Sullivan. Some interesting news here from Apple in advance of their new phone and possible device release in a few weeks. I applaud the move, but would like to see more information about data portability in the next release.
Science Advisor, Larry Smarr by 23andMe. Great to hear our friends 23andMe and Larry Smarr are getting together to help work on understanding Inflammatory Bowel Disease. If you’ve been diagnosed with Crohn’s disease or ulcerative colitis consider joining the study.
Personal Health Data: It’s Amazing Potential and Privacy Perils by Beth Kanter. A lot of people have been talking recently about the privacy implications of using different tracking tools and technologies. In this short post Beth opens up some interesting questions about why we might or might not open up our personal data to others. Make sure to read through for some insightful comments as well.
Let’s Talk About 3 Months of Self-Quantifying by Frank Rousseau. Frank is one of the founders of Cozy Cloud, a personal could service. He’s also designed Kyou a custom tracker system built on top of Cozy. He’s also been using the services to track his life. In this post he explain how tracking his activity, sleep, weight, and other habits led to some interesting insights about his behavior.
The iPhone 5S’ M7 Predictor as a Predictor of Fitbit Steps by Zach Jones. A great post here by Zach as he explores the data taken from his iPhone 5S vs. his Fitbit.
Using Open Data to Predict When You Might Get Your Next Parking Ticket by Ben Wellington. Not strictly a personal data show&tell here, but as someone who suffers from street sweeping parking tickets somewhat frequently I found this post fascinating. Now to see if Los Angeles has open data…
What Time of Day Do People Run? by Robert James Reese, Dan Fuehrer, and Christine Fennessay. Runners World and Runkeeper partnered to understand the running habits of runners around the world. Some interesting insights here!
What Happens When You Graduate and Get a Real Job by Reddit user matei1987. A really neat visualization of min-by-min level Fitbit step data.
Data + Design by Infoactive and the Donald W. Reynolds Institute. A really interesting and unique take on a data visualization book. This CC-licensed, open source, and collaborative project represents the work of many volunteers. I’ve only read through a few chapters, but it seems to be a wonderful resource for anyone working in data visualization.
Want to receive the weekly What We Are Reading posts in your inbox? We’ve set up a simple newsletter just for you. Click here to subscribe. Do you have a self-tracking story, visualization, or interesting link you want to share? Submit it now!
Enjoy this week’s list!
The Five Modes of Self-Tracking by Deborah Lupton. One of our favorite sociologists, Deborah Lupton, explores the typologies of self-trackers she’s identified for an upcoming paper. A very nice and clear explanation of the self-tracking practices in regards to different “loci of control.” (Make sure to also read Deborah’s great post, “Beyond the Quantified Self: The Reflexive Monitoring Self“)
In-Depth: How Activity Trackers are Finding Their Way Into the Clinic by MobiHealthNews. An interesting look at the recent influx FDA-cleared activity and movement trackers and how clinicians are looking to use them. Surprising to me is the lack of data access for the patient in these devices (at least on first glance).
The Reluctantly Quantified Parent by Erin Kissane. As a new mother, Erin was hesitant to use what she deemed “anxious technology.” After some hard nights of little sleep she began to slowly incorporate some self-tracking technology into her routine with her newborn daughter. A great read about using tools then putting them away once they’ve served their purpose. (Reminded me of this great talk by Yasmin Lucero.)
Returns to Leisure by Tom VanAntwerp. Tom was interested in his return on investment from his leisure time actives. He tracked his time spent in different non-work activities for two weeks and calculated the cost of participating in those activities.
The Quantified Microbiome Self By Carl Zimmer. The great science writer, Carl Zimmer, writes about a recent experiment and journal article by two MIT researchers who tracked their microbiome every day for a year. Fascinating findings, including a successful self-diagnosis of salmonella poisoning. You can also read the original research paper here.
Better Living Through Data by James Davenport. We recently highlighted one of James’ posts on how his laptop battery tracking led him to understand his computer use habits. In this post he dives deeper into the data.
A Personal Analysis of 1 Year of Using Citibike by Miles Grimshaw. Miles was interested in understanding more about his use of the Citibike bike share system in New York City. Using some ingenious methods he was able to download, visualize, and analyze his 268 total trips. I especially appreciate his addition of a simple “how-to” so other Citibike users can make the same visualizations.
Visualizing Runkeeper Data in R by Dan Goldin. In 2013 Dan ran 1000 miles and tracked them using the popular Runkeeper app. Runkeeper has a quick and easy data export function and Dan was able to download his data and use R to visualize and analyze his runs. (Bonus Link: If you’re a Runkeeper user you might be interested in this fantastic how-to for making a heatmap of your runs.)
This Week on Quantifiedself.com
Natty Hoffman: The Enlightened Consumer
QSEU14 Breakout: Passive Sensing With Smartphones
Jenny Tillotson: Science, Smell, and Fashion
Paul LaFontaine: We Never Fight on Wednesdays
Vanessa Sabino on Tracking a Year of Sleep
Last year Alex Collins was diagnosed with Type 1 diabetes. Prior to his diagnosis Alex was frequently engaged in different types of exercise and physical activity. After his diagnosis his doctor mentioned that he might have a hard time exercising and controlling his blood sugar to prevent hypoglycemia. In this talk, presented at the London QS meetup group, Alex described his process for tracking and understanding the data that affects his day-to-day life so that he could “live my life normally without a high risk of complications.” This process of collecting and analyzing data has even pushed him to continue to explore his athletic boundaries, resulting in a running a ultramarathon and setting the world record for the fastest marathon while running in an animal costume.
Slides are available here.
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.
There are no shortage of apps and devices to track our various physical activities. Going for run? A few laps at the pool? An early morning hike? All of these are trackable with data delivered and archived in a variety of different ways. Mike McDearmon loves to get outdoors, and he also loves tracking his activities. What started as a project to document his runs by taking a picture every time he went running has evolved into a fascinating mixed-media project. Since 2011 Mike has been taking a picture every time he exercises outdoors. In this talk, presented at the New York QS meetup group, Mike explains his methods, and digs a bit deeper into what this means to him.
For me, the real value in this whole project hasn’t necessarily come from the data at all, but from the process of getting outdoors, exploring my surroundings, taking photographs, and then reflecting on my experiences through documentation. This is what I feel is at the heart of the Quantified Self movement – it’s the passion and enjoyment in certain aspects of our lives that makes us want to document them in the first place. – from 300 Outings.
Download slides here.
I highly suggest taking the time to peruse Mike’s wonderful website where he documents his running, cycling, hiking, walking, and the pictures he’s talking along the way. He’s also built a really neat data dashboard that is worth perusing.
Julie Price began running marathons in 2002. While training and learning about running she began to pick up new “rules of thumb” to help guide her training and performance, but something was still missing. How did she know that she was sticking to these rules? Was there any evidence that training was working or that she was accomplishing what she wanted to? Julie started tracking her running using a variety of tools to help answer these questions and start understanding her running. Watch Julie’s presentation from the 2013 Quantified Self Global Conference to hear more about what she learned when she started tracking.
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.
Data gave me power to talk about the issue.
We highlight a lot of great show&tell talks here that focus on personal medical mysteries and understanding one’s own health. Well, this one really hit home for me. I’m a runner and I’m constantly battling minor injuries and recurring knee pain. It’s nothing terrible, but it’s at that level of annoying that really makes it hard to enjoy running as much as I should.
Mark Wilson was having similar issues. After running a half-marathon his knee started giving him trouble. The typical treatments didn’t work for him, but instead of giving up running he turned to self-tracking to understand his knee pain (you can see a snap shot of Mark’s running (blue) and knee pain (pink) over time in the header image of this post). In this show&tell talk, filmed at the QS San Francisco Meetup, Mark explains how he built a database that pulls information from different sources like Fitbit, Runkeeper, and his self-rated knee pain, and what he’s learned from that process.
I think most importantly putting all this data together and being able to look at it gave me power to talk about it. Because, I can’t really describe how much despair I was feeling just looking at my knee and thinking, “What the hell is wrong with you? Why is my knee hurting?” I felt like I was trying everything I could on my own and it just wasn’t working. So I wanted to collect a lot of evidence against my knee to indict it.
This data-backed indictment enabled him to have better and more productive conversations with his physical therapist and he began to understand how to move forward. Is it working? You’ll have to watch his great talk to find out: