Tag Archives: sleep
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
Enjoy these articles, examples, and visualizations!
OpenNotes: ’This is not a software package, this is a movement’ by Mike Milliard. I’ve been following the OpenNotes project for the last few years. There is probably no better source of meaningful personal data than a medical record and it’s been interesting to see how this innovative project has spread from a small trial in 2010 to millions of patients. This interview with Tom Delbanco, co-director of the OpenNotes project, is a great place to learn more about this innovative work.
Beyond Self-Tracking for Health – Quantified Self by Deb Wells. It was nice to see this flattering piece about the Quantified Self movement show up on the HIMSS website. For those of you looking to connect our work and the broader QS community with trends in healthcare and health IT you should start here.
So Much Data! How to Share the Wealth for Healthier Communities by Alonzo L. Plough. A great review of the new book, What Counts: Harnessing Data for America’s Communities, published by the Federal Reserve Bank of San Francisco and the Urban Institute. The book is available to read online and in pdf format.
The Ultimate Guide to Sleep Tracking by Jeff Mann. A great place to start if you’re interested in tracking sleep or just want to learn more about sleep tracking in general.
What RunKeeper data tells us about travel behavior by Eric Fischer. We linked to the recent collaboration between Runkeeper and Mapbox that resulted in an amazing render of 1.5 million activities a few weeks ago. The folks over at Mapbox aren’t just satisfied with making gorgeous maps though. In this post, Eric, a data artist and software developer at Mapbox dives into the data to see what questions he can answer.
General Wellness: Policy for Low Risk Devices – Draft Guidance for Industry and Food and Drug Administration Staff . On Friday, January 16, 2015, the Food and Drug Administration released a draft of their current approach to regulating “low risk products that promote a healthy lifestyle.” These guidelines point to a stance that will allow many of the typical self-tracking tools currently in use today to remain outside the regulations normally associated with medical devices. (A quick overview of this document is also available from our friends at MobiHealthNews)
The Great Caffeine Conundrum. A wonderfully thorough post about using the scientific process, statistics, and self-tracking data (Jawbone UP) to answer a seemingly simple question, “Does eliminating caffeine consumption help me sleep better?”
Four Years of Quantified Reading by Shrivats Iyer. Shrivels has been tracking his reading for the last four years. In this post he explains his process and some of the data he’s collected, with a special emphasis on what he’s learned from his 2014 reading behavior.
Pretty Colors by Chanlder Abraham. Chandler spent his holiday break exploring his messaging history and creating some amazing visualizations. Above you see a representation of his messaging history with the 25 most contacted people since he’s began collecting data in 2007.
Heart Rate During Marriage Proposal by Reddit user ao11112. Inspired by another similar project, this ingenious individual convinced his now fiancé to wear a hear rate monitor during a hike. Unbeknownst to her, he also proposed. This is her annotated heart rate profile.
Help CDC Visualize Vital Statistics by Paula A. Braun. The CDC has a new project based on the idea that better visualization can make the data they have more impactful. If you’re a data visualizer or design consider downloading the CDC Vital Statistics Data and joining #vitalstatsviz.
From the Forum
Join us at our upcoming QS15 Global Conference and Exposition on June 18-20 in San Francisco to learn how to use self-tracking tools to aid in recovery and get back into a productive lifestyle without overdoing it.
Maggie Delano was diagosed with Post Concussion Syndrome (PCS) after hitting her head over Labor Day Weekend. To recover, she had to give her brain a break from anything too cognitively stimulating, such as using screens, reading, intense physical exercise, and loud music. Maggie was able to return to work after several weeks off. She has developed strategies that balance getting work done with giving her brain a rest and preventing burnout. She’s been using apps such as Awareness to keep her mindful of how much time she’s spending on her computer, HabitRPG to slowly build back up her prior habits and self-tracking, and Beddit to help figure out what allows her to sleep best.
Maggie’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. 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!
Benn Finn has been battling issues with his sleep ever since he was a teenager. His sleep was suffering from the usual problems we’ve all faced: taking too long to get to sleep, waking up too often, waking up late, and being tired during the day. He made plan to fix his issues by researching what affects sleep and then experimenting to find out what worked for him. For four months he tracked his sleep using Sleep Cycle along with 21 factors that he thought might affect his sleep. He also created a “sleep quality” score based on 5 different data points, including data from the Sleep Cycle app. In this talk, presented at the London QS meetup group, Ben describes his experiments, what he learned from analyzing his data, and how he finally ended up fixing his sleep issues. (Special thank you to Ken Snyder for his valuable work documenting the talks at QS London.)
Slides are also available here.
We hope you enjoy this week’s list of articles, posts, show&tell descriptions, and visualizations!
I’m Terrified of My New TV: Why I’m Scared to Turn This Thing On — And You’d Be, Too by Michael Price. Michael, a lawyer at the Brennan Center for Justice at the NYU School of Law, describes his experiences with his new “smart” TV. More sensors means more records being stored somewhere you might not have access to. Especially interesting when your device picks up every word you say:
“But the service comes with a rather ominous warning: ‘Please be aware that if your spoken words include personal or other sensitive information, that information will be among the data captured and transmitted to a third party.’ Got that? Don’t say personal or sensitive stuff in front of the TV.”
Public Perceptions of Privacy and Security in the Post-Snowden Era by Mary Madden. A great report from the Pew Research Internet Project. I don’t want to give away any of the juicy stats so head over and read the executive summary.
This Is What Happens When Scientists Go Surfing by Nate Hoppes. It’s not all privacy talk this week. This is a fun article exploring how new sensors and systems are being used to monitor surfers as they train and practice.
How Private Data is Helping Cities Build Better Bike Routes by Shaun Courtney. We covered the new wave of personal data systems and tools feeding data back into public institutions a bit before. Interesting to hear that more cities are investing in understanding their citizens through the data they’re already collecting.
What Do Metrics Want? How Quantification Prescribes Social Interaction on Facebook by Benjamin Grosser. Ben is most commonly known around the QS community as the man behind the Facebook Demetricator, a tool to strip numbers from the Facebook user interface. In this article, published in Computational Culture, he lays out an interesting argument for how Facebook has created a system in which the users, “reimagine both self and friendship in quantitative terms, and situates them within a graphopticon, a self-induced audit of metricated social performance where the many watch the metrics of the many.”
The Cubicle Gym by Gregory Ferenstein. Gregory was overweight, overworked, and in pain. He started a series of experiments to improve his help, productivity, and wellbeing. I enjoyed his mention of using the Quantified Mind website to track cognition. If you find his experience interesting make sure to read a previous piece where he explains what happened when he replaced coffee with exercise.
Maximizing Sleep with Plotly and Sleep Cycle by Instructables user make_it_or_leave_it. A really nice step by step process and example here of graphing an making sense of Sleep Cycle data.
Toilet Matters by Chris Speed. A super interesting post on what a family was able to learn by having access to data on of all things, the amount of toilet paper left on a roll and when it was being used. Don’t forget to read all the way to end so you can get to gems like this:
“[…]the important note is that the source of this data is not only personal to me, it is also owned by me. We built the toilet roll holder and I own the data. There are very few products or smart phone apps that I can say the same about. Usually I find myself agreeing to all manner of data agreements in order to get the ‘free’ software that is on offer. The toilet roll holder is then my first experience of producing data that I own and that I have the potential to begin to trade with.“
E-Traces by Lesia Trubat. A beautiful and fun project by recently graduated design student, Lesia Trubat. Using adruinos and sensors places on the shoes of dances she was able to create unique visualizations of dance movement. Be sure to watch the video here.
Animated Abstractions of Human Data by James E. Pricer. James is an artist working on exposing self-collected data in new and interesting ways. Click through to see a dozen videos based on different types of data. The image above is a capture from a video based on genotypes derived from a 23anMe dataset.
The Great Wave of Kanagawa by Manuel Lima. Although this is an essay I’m placing it here in the visualization section because of it’s importance for those working on the design and delivery of data visualizations. Manuel uses the Great Wave off Kanagawa as a wonderful metaphor for designing how we visually experience data.
D3 Deconstructor by UC Berkeley VisLab. A really neat tool here for extracting and repurposing the data powering at D3.js based visualization.
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 June 18-20 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!
A long one this time. Enjoy the words, numbers, and images herein.
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.
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!
Schedule Abstracted by Mike McDearmon.
Even a hectic schedule can have a sense of serenity with all text, labels, and interface elements removed.
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?
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!
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.
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.
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.
It’s About Time by Hunter Whitney. A nice post here about the different methods of visualizing temporal data.
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)
Like many people, Christel de Maeyer felt that her sleep could be better. Presenting at our 2013 conference in Europe, Christel shares what she learned from collecting over three years of sleep data.
What did Christel do?
Christel tracked her sleep for 2 years with various devices. She tested the effects of different variables on her sleep quality, including consumption of alcohol, keeping a consistent wake time and changing her mattress.
How did she do it?
She used the Zeo to track sleep for two years, before switching over to a BodyMedia device. While making changes she monitored how her sleep data changed, as well as how she felt.
What did she learn?
Before self-tracking, Christel felt that she woke up frequently during the night, and the Zeo confirmed this. On average she woke up around 8 to 9 times. She suspected the mattress could be part of the problem. After considerable research, she replaced her mattress (to one that had a foam top), successfully reducing her wake-ups to 4 or 5.
Christel discovered that her sleep patterns looked significantly different after just two glasses of alcohol. Her REM diminishes to nearly 0% (though deep sleep seems unaffected).
Christel also found that total sleep time was less important for how she felt the next day than the combination of REM and deep sleep. Even if she only sleeps for six hours, as long as she gets at least 2 hours of combined REM/deep sleep, she feels good.
In addition to these findings and others she explores in the video above, Christel has taken her lessons and now helps others with sleeping issues. You can find more at her website.
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.