Topic Archives: What We’re Reading

What We Are Reading

It’s link-apolooza time! Enjoy these great news pieces, blog posts, personal data stories, and visualizations.

Articles

Robert Wood Johnson Foundation Launches Initiative to Assess How Data Can Be Used to Improve Health by RWJF Staff. Some exciting news coming out of RWJF this week about their new program to explore how individuals and communities are using health data and information. Don’t forget to read the accompanying blog post to learn more.

“For These Times”: Dickens on Big Data by Irina Raicu. Who knew the philosophical debate on a life governed by measurable facts had such a pedigree!

How and Why We Are Working with the FDA: Background and a Brief Summary of the Recent Meeting with the FDA about the Nightscout Project by Scott Leibrand. We’re big fans of the Nightscout project here at QS Labs. It’s great to seem them moving forward with a productive dialogue with the FDA.

Sir Tim Berners-Lee Speaks Out on Data Ownership by Alex Hern.

The data we create about ourselves should be owned by each of us, not by the large companies that harvest it, Tim Berners-Lee, the inventor of the world wide web, said today.

Sensors and Sensibility by Andrew Leonard. One day we might look back at our fears of insurers nefariously using our data to adjust premiums. Until then, that fear is alive and real. Thorough reporting here from the new Backchannel.

One Quantified Self App To Rule Them All by Chris Roth. As Chris explored the growing QS space and worked on his own open-source logging app he noticed a few things. Read on to see his take on where the space should be evolving.

Quantified Health and Software Apps by Sara K. Moir. What started as a Tweetstorm about her experience with MyFitnessPal expanded into a great exploration about what it means to be a user (and designer) of health behavior tracking tools.

Show&Tell

AZ_timetext2
How Text Messages Change from Dating to Marriage by Alice Zhao. Only a data scientist would celebrate a six-year anniversary with a thoughtful and thorough analysis of their communication. Alice did a great job here showing what’s changed over the years as her and her husband have moved from courtship to marriage.

ZT_Weight_small
Losing 58.3 Lbs For Science by Zachary Townsend. Zachary just finished up his participation in the One Diet Does Not Fit All: Weight Loss study. Over the last year he’s lost nearly 60lbs and learned a lot about himself and his diet.

Using JSL to import BodyMedia Fit Activity monitor data into JMP by Shannon Conners. We featured Shannon’s amazing visualization work in our September 20th edition of What We’re Reading. She returns here with a thorough how-to on how to explore BodyMedia and MyFitnessPal data in JMP. Even as a non-JMP user I was delighted to find out about the MyFitnessPal Data Downloader Chrome Extension she used to download her meal data.

Visualizations
AG-weekly-skyline-graph
My Up Skyline for the Week by Abe Gong. Abe is a data scientist at Jawbone was taking a look at his own activity data and decided to use the then new Jawbone API to download his data and make some interesting visualizations.

ER_SolarEclipses
Your Life on Earth by the BBC. Not a typical QS visualization, but unique and interesting to see what’s happened in and around the world over the course of your life.

I’ve been exploring upgrading my data visualization skills by learning D3. If you’re in the same boat or want know someone who is then you can point them towards this great intro from the engineers at Square.

From the Forum

Decode Your Chronic Illness
The Ethics of QS
Tasks & Measures
Lifelogging to Prevent Depression
Wearable Body Temperature Tool
Sleep Apnea Treatments
Looking for Android Time Tracking App

Today’s Number is 35: The age of the spreadsheet!

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What We Are Reading

A long one this time. Enjoy the words, numbers, and images herein.

Articles
New biometric tests invade the NBA by Pablo S. Torre and Tom Haberstroh. Data and statistics are nothing new in professional sports. They’ve even made Academy Award nominated movies based the idea that data can help a team win. Until now data on players and teams has come from analysis of practices and gameplay. This great piece opens another discussion about collecting even more personal data about how players in the NBA live their lives off the court. Recall that athletes, coaches, and owners have been talking about out of game data tracking since 2012.

Misleading With Statistics by Eric Portelance. We’ve featured these type of articles before, but the example used here by Eric is not to be missed. So many times the data visualization trumps the actual data when a designer makes editorial choices. After reading this piece you’ll think critically the next time you see a simple line chart.

Handy Tools & Apps by Ray Maker. A great resource for athletes and exercisers who use a variety of tools to capture, export, and work with the activity and workout data we’re collecting.

You are not your browser history by Jer Thorpe. If someone you didn’t know was given a record of every ad served to you in your browser, what would they say about you? Who would they think you were? Jer Thorpe actually put these questions to the test as part of his work with the Floodwatch project. Floodwatch is a very interesting tool (browser extension) that saves and visualizes the adds you see while you browse. They also have a clear privacy policy including giving you access to your data.

Show&Tell
Happiness Logging: One Year In by Jeff Kaufman. A great post here about what Jeff has learned about himself, what is means to log something like “happiness”, and the power of tagging data. After looking at his data, and a commenter’s from the r/quantifiedself subreddit, I’m wondering about the validity of 10-point scales for this type of self-tracking.

Redshit/f.lux Sleep Experiment by Gwern. Our esteemed friend and amazing experimenter is back with another analysis of his sleep data. This time he explains his findings from using a program that shifts the color temperature on his computer away from blue and towards red.

I ran a randomized experiment with a free program (Redshift) which reddens screens at night to avoid tampering with melatonin secretion and sleep from 2012-2013, measuring sleep changes with my Zeo. With 533 days of data, the main result is that Redshift causes me to go to sleep half an hour earlier but otherwise does not improve sleep quality.

Make sure to join the discussion on the forum!

Visualizations

Joost_3yr
3 Years of computing by Joost Plattel. Our good friend and Amsterdam QS co-organizer, Joost Plattel takes a look at three years of running Lifeslice.

ScheduleAbstracted_MMcD
Schedule Abstracted by Mike McDearmon.

Even a hectic schedule can have a sense of serenity with all text, labels, and interface elements removed.

LocationHistory
Location History Visualizer by Theo Platt. The data above is actually my full Location History from Google Takeout. Theo made this simple and fast mapping visualization tool. Try is out yourself!

Lifelogging Lab. No visualizations here, but if you’re a designer, visualizer, or just have some neat data then you should submit it to this sure to amazing curated exhibition.

From the Forum
The ethics of QS
Call For Papers: HCI International 2015 Los Angeles
Pebble for Fitness Tracking
QS Business Models
QS, Light, Sleep, Reaction Timing, and the Quantified Us
Are you using your data to write a reference book or tell a story?

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What We Are Reading

We’ve put together an nice list of articles for you to enjoy this weekend. As always, please get in touch if you have something you’d like us to share!

Articles
Finding Patterns in Personal Data by Kitty Ireland. Another great post from Kitty about using personal data to uncover interesting, and sometimes surprising, patterns. Some great examples in this post!

The Tale of a Fitness-Tracking Addict’s Struggles With Strava by Jeff Foss. Just because you can track, and you can get something out of it, might not mean you should. (I had a similar experience on a recent trip to Yosemite so this article was quite timely.)

Algorithmic skin: health-tracking technologies, personal analytics and the biopedagogies of digitized health and physical education by Ben Williamson. Quantified Self and self-tracking tools are not limited to only being used by conscious and willing adults. They’re also being developed for and used by a growing number of children and adolescents. What does this mean of health and fitness education, and how should we think about algorithms in the classroom and gym?

Seeing Ourselves Through Technology: How We Use Selfies, Blogs and Wearable Devices to See and Shape Ourselves by Jill Walker Rettberg. I just started this book and it appears offer some interesting perspectives on the current cultural shift toward technically mediated representation. The book includes a chapter on Quantified Self and is available for download in PDF and EPUB under a CC BY license.

Show&Tell
Why Log Your Food by Amit Jakhu. Amit started tracking his food in March (2014) and has since learned a few things about his preconceived notions about his diet, food, and what it takes to keep track of it all.

Even When I’m active, I’m sedentary by Gary Wolf. Gary and I used our recently released QS Access app to download his historical step data. Using some simple charting in Excel we found some interesting patterns related to his daily movement.

Visualizations
SleepJewel
When Do I Sleep Best by Jewel Loree. Jewel presented her sleep tracking project at a recent Seattle QS Meetup. The image above is just a small piece of a great set of visualizations of her data gathered with SleepCycle and Reporter apps.

20min
Lightbeam Visualization by Simone Roth. Interesting tool described here to track how your data and web activity is being tracked. You can check out the Firefox extension here.

Minard It’s About Time by Hunter Whitney. A nice post here about the different methods of visualizing temporal data.

Respiration Machine 0.3 (bellows) by Willem Besselink. A neat physical visualization and art project that represents breath using a Hoberman sphere.

From the Forum

There has been a lot of great discussion on the forum lately. Check out some of the newest and most interesting topics below.

QS Access App
Hypoxic – An App for Breathing Exercises with HRV Tracking
Sleep Tracking & Hacking Google Hangout
Personal Analytics Service for Software Developers
Using Facial Images to Determine BMI
The Right Tool? (tracking and plotting sleep)

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What We Are Reading

We hope you enjoy this weeks list. Feel free to submit articles, show&tell self-tracking stories, and QS data visualizations. Just email me!

Articles
Why can’t you track periods in Apple’s Health app? by Nat Buckley. With the recent re-release of Apple’s HealthKit enabled self-tracking and personal data system it no wonder that people are taking a long hard look at what data is being excluded. With the popularity of menstruation tracking apps (this app has nearly 30,000 ratings) it’s surprising this was overlooked. This excellent post is a must read on the topic.

Now That Cars Have Black Boxes, Am I Being Tracked? by Popular Science Editors. Questions and concerns about surveillance are becoming more commonplace. As someone who is looking to purchase a car in the next year or so I was happy to see this post come across my stream.

The Quantified Self community, lifelogging and the making of “smart” publics by Aristea Fotopoulou. I love it when people take a thoughtful look at the Quantified Self community and write about their experiences:

For me, the potential of QS for public participation lies in the show and tell meet-ups that constitute a central feature of this community. Meet-ups enable the exchange of stories about the success or failure of lifelogging practices; they allow people to connect and form synergies around common interests, and to explore wider questions such as personal data management and ownership. [...] members touch upon key political issues and create temporary spaces of dialogue: what happens to personal data, who has access to these data (is it private individuals, governments or corporations)? For what purposes (medical research)? And how can these data be interpreted (by algorithms, visualisations) and used to tell stories about people?

Stepping Down: Rethinking the Fitness Tracker by Sara M. Watson. Sara uses her personal journey of recovery from hip surgery to frame an interesting question: Should we trust our fitness trackers to prescribe movement goals?

Show&Tell
Practical Statistical Modeling: The Dreaded After-School Carpool Pickup by Jamie Todd Rubin. Jamie wanted to understand if there was a way he could reduce how much time he spent waiting in line to pick up his son from school. Why not track it and model it!

Bulletproof Diet and Intermittent Fasting: 1.5 Year Results by Bob Troia. Bob takes a deep dive into his data to see if this particular diet is having beneficial health effects. Click for the great data, stay for the wonderful discussion and very, very thorough write-up.

Visualizations


Quotidian Record by Brian House. I’ve been a fan of Brian House since his early days visualizing Fitbit data. I was reminded of this work during a conversation about geolocation data and thought it would be a nice addition to our visualization list.

KMcCurdy_SMVisualizing My Daily Self-Management by Katie McCurdy.

What does my daily medication and self-management look like? How could I visualize this regimen? How can I communicate the ‘burden’ and work of caring for myself?

I decided to draw pictures of the things that I need to do on a daily basis; that way I could show the workshop attendees what my day was like instead of just telling them.

JawboneTimetoEatIt’s Time to Eat by Karl Krehbiel. Karl, a data science intern at Jawbone used the data from their global community of users the determine the likelihood of food and drink consumption during the day. Really fun and interesting visualizations here.

From the Forum
Seeking opinions of diabetic self-trackers for non-profit project
Five Years of Weight Tracking
What Disclaimer should I use when making my personal #quantifiedself data public?

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What We Are Reading

We hope you enjoy this week’s list!

Articles
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.

Show&Tell
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!

Visualizations
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!

SC_calorieweight

SC_sleep

Tracking Energy use at home by reddit user mackstann.

EnergyApp

“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).”

From the Forum
Help With Livestrong Data Export
Need Help Deciding Which Device
New to Fitness Tracking

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What We Are Reading

Before we get to this week’s list we want to make sure you know about our recent conference announcement. This week we announced our QS15 Conference & Exposition. This will be our seventh conference and is sure to be an amazing event. We invite you to register today!

Now on with the good stuff!

Articles
Why Big Data Won’t Cure Us by Gina Neff. A great research paper in the aptly name journal, Big Data. Dr. Neff specifically focuses on the perils of assuming “all the data” will solve the numerous health healthcare problems and then lays out five elements to consider as data, big and small, becomes part of our healthcare experience.

More Than Meets the Eye: NASA Scientists Listen to Data by Kasha Patel. Apparently the scientists studying the sun have so much data to sift through that listening to signals is a valuable alternative to visualizing it. (via our friend Joost Plattel)

Quantified Dating, Relationships, and Sex by Kitty Ireland. A great series of three posts by Kitty that explores a variety of examples of using self-tracking in the most intimate of situations – dating, long-term relationships, and sex.

A Look Back At the Evolution of Wearable Tech. In the wake of the recent Apple Watch announcement I love being able to look back at the history of different how technology has made inroads into our lives.

Show&Tell
The Baby Measureur by Erich Morisse. Erich is a proud father of a new child and like any new dad with data skills he started tracking some important metrics such as feeding time, feeding duration, and of course diaper changing!

A Day at Burning Man, Visualized Through Health Tracker Data by Gregory Ferenstein. Gregory takes his Basis Band to Burning Man and shows us what he learned.

Visualizations
scotto-prism
My Most Intimate Self Portrait by Scott Ogle. Scott has a wonderful post here about a visualization of his almost 30,000 text messages.

If I look closely, I can see a new job, vacations and a death in the data. I can even see where I moved past it all and stopped feeling the need to communicate so much. It may just be text messages, but it all correlates to things that are really real.

And all of it is captured in this graph.

AmsterdamMap
9 Days in Amsterdam – Tracking my Mobility in Bicycle Wonderland by Patrick Stotz. Patrick traveled to Amsterdam and tracked his stay using OpenPaths. I especially enjoyed how he was able to segment his means of transportation. If you’re interested in maps I suggest take a look at his great checklist for making geodata visualizations and this list of geodata tools.

RunkeeperTime
What Time of Day Do People Run by Data @ Runkeeper. As a runner I can’t get enough of these visualizations and data analyses.

From the Forum
How to Replicate SleepCycle?
What Application Can Monitor My Levels of Energy?
HealthKit
Quantified Baby

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What We Are Reading

We hope you enjoy this week’s list!

Articles
Are Google making money from your exercise data?: Exercise activity as digital labour by Christopher Till. Christopher describes his recent paper, Exercise as Labour: Quantified Self and the Transformation of Exercise into Labour, which lays out a compelling argument for considering what happens when all of our exercise and activity data become comparable. Are we destined to become laborers producing an expanding commercialization of our physical activities and the data they produce?

How Big is the Human Genome? by Reid J. Robinson. Prompted by a recent conversation at QS Labs, I went looking for information about the size of the human genome. This post was one of the most clear descriptions I was able to find.

Show&Tell

VacationGPS
Visualizing Summer Travels by Geoff Boeing. A mix of Show&Tell and visualization here. Geoff is a graduate student and as part of his current studies he’s exploring mapping and visualization techniques. If you’re interested in mapping your personal GPS data, especially OpenPaths data, Geoff has posted a variety of tutorials you can use.

Visualizations

SymptomViz
Symptom Portraits by Virgil Wong. For 30 weeks Virgil met with patients and helped them turn their symptoms into piece of art work and data visualization.

Data Visualization Rules, 1915 by Ben Schmidt. In 1915, the US Bureau of the Census published a set of rules for graphic presentation. A great find by Ben here.

From the Forum
Moodprint
Measuring Cognitive Performance
Looking Forward to Experimenting

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What We Are Reading

Enjoy this week’s list!

Articles
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.

Show&Tell
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…

Visualizations
RWTime
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!

FitbitMin
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.

DataDesign
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.

From the Forum
Good Morning World!
Quantified Chess
New Activity Tracker to Replace BodyMedia?
Indirect Mood Measures
OPI TrueSense for Sleep Tracking

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!

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What We’re Reading

Ernesto is out for this round, so I’m filling in. I hope you enjoy this week’s list of articles, show&tells and visualizations!

Articles
“Standing Up for American Innovation and Your Privacy in the Digital Age” by Senator Ron Wyden. Access to your personal data is something that we care about and has been a topic of conversation at QS meetups and conferences. During Portland’s recent TechFestNW, Oregon Senator Ron Wyden took a strong stance on the nature of the relationship of the user and his/her data by criticizing the “Third-Party doctrine”.

Digital Health State of the Industry by MobileHealthNews.  In the hype-filled world of digital health, MobiHealthNews is one of the (few) sources we trust for business reports. Their latest quarterly roundup is very well done, as always.

Show&Tell
Better Living Through Data by James Davenport. James has over four years of battery log data from three laptops. By looking at the data, he saw a view of his own computer usage as well as a glimpse of his laptop’s secret life in the middle of the night. If you want to keep logs of your laptop’s battery, you can use the same script.

Visualizations
Which_Cities_Get_the_Most_Sleep__-_WSJ_com 2Which_Cities_Get_the_Most_Sleep__-_WSJ_com

Which Cities get the most sleep? by Stuart A. Thompson. We showed a visualization last week that used UP user data. This visualization is from the same dataset, but I couldn’t pass up showing it because the sleep/step pattern contrast between New York and Orlando is so interesting.

From the Forum
OPI TrueSense for Sleep Tracking
Report App Question
What is your opinion on neurofeedback?

This Week on Quantifiedself.com
Cors Brinkman: Lifelog as Self-Portrait
Eric Boyd: Tracking My Daily Rhythm With a Nike FuelBand
Kevin Krejci: An Update on Tracking Parkinson’s Disease
Mark Drangsholt: Deciphering My Brain Fog
Mark Leavitt: Whipping up My Willpower

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!

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What We’re Reading

It’s a long one today, so buckle in and get ready for some great stuff!

Articles
The Quantified Self: Bringing Science into Everyday Life, One Measurement at a Time by Jessica Wilson. This piece, from the Science in Society Office at Northwestern University, explores the Quantified Self movement, with a particular focus on the local Chicago QS meetup. Always interesting to see how individuals draw distinctions between self-tracking projects and “real science.”

Diversity of Various Tech Companies By the Numbers by Nick Heer. Recently Apple released data about the diversity of their employee workforce. This marked the last major tech company to publish data about diversity. In this short post Nick takes that data and shows how it compares to data from the US Bureau of Labor Statistics. Interested in more than just the big six listed here? Check out this great site for more tech company diversity data (Hat tip to Mark Allen for finding that link!)

Intel Explores Wearables for Parkinson’s Research by Christina Farr, Reuters. Intel is in the news lately based on their interest in developing and using their technological prowess for qs-related activities. In this post/press release, they describe how they’re partnering with the Michael J. Fox Foundation to explore how they can use wearable devices to track and better understand patients with Parkinson’s Disease. It appears they’re also working to get their headphone heart rate tracking technology out to market.

Spying on Myself by Richard J. Anderson. I’m always interested in how people talk to themselves about self-tracking. This short essay describes the tools that Richard uses and why he continues or discontinues using them. His follow up is also a must read.

Dexcom Mac Dance by Kerri Sparling. You know we’re fascinated by the techniques and tools developed and refined by the the diabetes community. In this short post, Kerri highlights the work of Brian Bosh, who developed a Chrome extension to access and download data from Dexcom continuous glucose monitors on a Mac. (Bonus link: Listen to Chris Snider’s great podcast episode where he talks to John Costik, one of the originators of the CGM in the Cloud/Nightscout project.)

Show&Tell
The Three-Year Long Time Tracking Experiment by Lighton Phiri. Lighton is a graduate student at the University of Capetown. In 2011 he became curious about how he was spending his time. After installing a time-tracking tool on his various computers, he started gathering data. Recently, after 3 years of tracking, he downloaded and analyzed his data. Read this excellent post to find out what he learned.

Experimenting with Sleep by Gwern. One of our favorite self-experimenters is back with some more detailed analysis of his various sleep tracking experiments. Read on to see what he learned about how caffeine pills, alcohol, bedtime, and wake uptime affects his sleep.

QS Bits and Bobs by Adam Johnson. Adam gave talk at a recent QS Oxford Meetup about his lifelogging and self-tracking, his custom tools for importing data to his calendar, and what he’s learned from his experiences. Make sure to also check out the neat tool he’s developed to log events to Google Calendar.

Visualizations

NikeFibers
FuelBand Fibers by Variable. A design team was given Nike FuelBand data from seven different runners and created this interesting visualization of their daily activity.

SleepWork
I don’t Sleep That Well: A Year of Logging When I Sleep and When I’m at Work by Reddit user mvuljlst. Posting on the r/dataisbeautiful subreddit, this user tracked a year of their sleep and location data using Sleepbot and Moves. If you have similar data and are interested in exploring your own visualization the code is also available.

JawboneCity
In the City that We Love by Brian Wilt/Jawbone. The data science team at Jawbone continues to impress with their production of meaningful and interesting data visualizations based on data from UP users. In this post and corresponding visualizations they explore the daily patterns of people from around the world. Make sure to read the technical notes!

From the Forum
Export Moves Data to Day One
Understanding Patents – All your transmission data belong to us
Quantified Self, It’s Benefits
Sun Exposure and Vitamin D Levels Wearable Tracker

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!

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