Paul LaFontaine: Heart Rate Variability and Flow

Paul LaFontaine is on an incredible journey to understand himself, his stress, and how he works through consistent examination of his heart rate variability (HRV). We’ve featured a few of his talks here on the Quantified Self website, and we were happy to have him present at a Bay Area QS meetup this past December. In this talk, Paul describes how he experimented with cognitive testing and recording his HRV to better understand if he was in a Flow state, and how to attain that balance between challenge and skill. Some very interesting personal conclusions about the role of belief in one’s own abilities versus actual skills.

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Meetups This Week

Eight wonderful QS meetup groups will be getting together this week in four different countries. Belfast and New Orleans are two new groups that will be having their very first events. Belfast is starting especially strong with a mother and son show&tell on using a new continuous glucose monitor system that doesn’t require finger prick calibration. Vienna will be playing with the meeting format by experimenting with an unconference style for their event.

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! If you organize a QS meetup, please post pictures of your event to the Meetup website. We love seeing them.

Monday, January 26
Seattle, Washington

Tuesday, January 27
Houston, Texas
Los Angeles, California
New Orleans, Louisiana

Wednesday, January 28
Ann Arbor, Michigan
Belfast, Northern Ireland

Thursday, January 29
Porto, Portugal
Vienna, Austria

 

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What We Are Reading

Below you’ll find this week’s selection of interesting bits and pieces from around the web. Enjoy!

Articles
Open Books: The E-Reader Reads You by Rob Horning. A fantastic essay about the nature of delight and discovery, and how that may (is) changing due to data collected from e-readers. For those interested in books and data this article By Buzzfeed’s Joseph Bernstein is also an interesting read.

Flashing lights in the quantified self-city-nation by Matthew W. Wilson. Quantified Self, smart cities, and Kanye West quotes – this commentary in the Regional Studies, Regional Science journal has it all. Read closely, especially the final paragraph, which gives space to think about the role the institutions and companies that provide cities with the means to “be smart” have in our in social and urban spaces.

Most Wearable Technology Has Been a Commercial Failure, Says Historian by Madeleine Monson-Rosen. This is a interesting book review for Susan Elizabeth Ryan’s Garments of Paradise which had me thinking about the nature of wearables, customization, and expression.

‘The Cloud’ and Other Dangerous Metaphors by Tim Hwang and Karen Levy. This was mentioned so many times over the last few days by so many smart friends and colleagues that I had to set aside time to read it. It was time well spent. The authors make the case that how we talk about data (personal, public, mechanical, and bioligical) is tied to the metaphors we use, and how those metaphors can either help or hinder the broader ethical and cultural questions we find ourselves grappling with.

Why the Internet Should Be a Public Resource by Philip N. Howard. This isn’t the first, nor will it be the last, argument for changing the way we think about and regulate the Internet. Worth reading the whole things, but in case you don’t consider this point:

And then we might even imagine an internet of things as a public resource that donates data flows, processing time, and bandwidth to non-profits, churches, civic groups, public health experts, academics, and communities in need.

Computers Are Learning How To Treat Illnesses By Playing Poker And Atari by Oliver Roeder. How does research into algorithms and AI intended for winning poker games morph into something that can optimize insulin treatment? An interesting exploration on the background and future implications of computers that can learn how to play games.

Data Stories #45 With Nicholas Felton. by Enrico Bertini and Moritz Stefaner. In this episode of the great Data Stories podcast Nicholas Felton talks about his background, his interest in typography, and what led him to start producing personal annual reports. Super fun to listen to them geek out about the tools Nicholas uses to track himself.

Increasingly, people are tracking their every move by Mark Mann. A great peak into some of our QS Toronto community members and how they use self-tracking.

Quantified Existentialism by Ernesto Ramirez. I’m putting this last here because it feels a bit self-congratulatory. Earlier this week I took some time to examine how common it is for people to express their relationship with what counts when they use self-tracking tools. It was a fun exercise.

Show&Tell
Insights From User Generated Heart Rate Variability Data by Marco Altini. While not a personal show&tell (however, I’m sure his data is in there somewhere), this great post details what Marco was able to learn about HRV based on 230 users and 13,758 recordings of HRV.

Quantify This Thursday: No Coding Required by Kerri MacKay. A bit different post here, more of a how-to, but I found it really compelling the lengths Kerri went to get get her Fitbit data to show up on he Pebble watch. I was especially drawn to her explanation of why this method is important to her:

The reality is, getting nudges every time I look at the clock or dismiss a text notification on my Pebble (via my step count) is yet another way to make the wearing-a-wearable less passive and the data meaningful.

Correlating Weight with Blood Pressure by Sam. A short and simple post detailing how Sam used Zenobase and his iHealth devices to see how weight loss was associated with his blood pressure.

Visualizations
WithingHolidays
The Effect of End of Year Festivities on Health Habits by Withings. The above is just one of four great visualizations from Withings exploring how the holidays affect how users sleep, move, and weight themselves. Unsurprisingly people are less likely to weight themselves on Christmas day (I looked at my data, I am among those non-weighers).

SimonData
Simon Buechi: In Pure Data by Simon Buechi. A simple, elegant dashboard intended to represent himself to the world.

MatYancy_Coding
Grad School Coding Analysis by Matt Yancey. The above is just a preview of two fantastic visualizations that summarize the coding Matt did while enrolled in the Northewestern Masters of Analytics program.

Fitbit_NewYears_Steps
News Year’s Eve Celebration in Steps by Lenna K./Fitbit. A fun visualization describing differences in how people in different age groups moved while celebrating the new year.

From The Forum
How do I visualize information quickly? (mobile app)
Monitoring Daily Emotions
Best Heartrate Monitor that syncs with Withings Ecosystem
Is the BodyMedia Fit still alive?
Capture Online Activities (and More) into Day One Journal Software (Mac/iOS)

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QS Access: Self-Report & Quantified Self in Health Research

As part of our new Access channel we’re going to highlight interesting stories, ideas, and research related to self-tracking data and data access issues and the role they take in personal and public health. We recently found this expert report, published in the International Journal of Obesity, that tackles issues with the data researchers rely on for understanding diet and physical activity behaviors, and ultimately concludes that the data is fundamentally flawed.

Researchers has known for a long time that relying on individuals to understand, recall, and accurately report what they eat and how much they exercise isn’t the best way to understand the realities of everyday life. Unfortunately for many years, this was the only way to track this information – interviews, surveys, and research measures. Only recently have tools, devices, and methods matured to a point where objective information can be captured and analyzed.

The authors of this article make the case that obesity and weight management fundamentally relies on getting these numbers right, and unfortunately most research hasn’t. Reading the background on self-report data and the call to action the authors make for developing and using more objective measures we can’t help but wonder about the role of commercial personal self-tracking tools. How can we, as a community of users, toolmakers, and researchers work together to open up access pathways so that the millions of people tacking pictures of their meals and uploading their step data can have a positive impact on personal and public health? This is an open question, one that we’re excited to be working on.

If you’re interested in these type of questions, or working on projects related to data access we invite you to get in touch and keep following along here with us.

 

 

 

 

 

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QS Access: Ian Eslick on Personal Experimentation

“Science is really about repeatability, about process, about discipline, about characterization, about controlling noise, and there are lot of different mechanisms that we can pull together to tell a story or inform a decision.”- Ian Eslick

This past April we were lucky to host a meeting of researchers, toolmakers, science funders, and government representatives for our first Quantified Self Public Health Symposium. This one-day meeting, and the work leading up to it, helped to shape our thoughts and ideas around what data access means and how it can be used to shape personal and public health. Access can take on a variety of different meanings from being able to obtain a copy of your data, to being able to contribute to and use public data sets. But access doesn’t always have to deal with the transfer of bytes of information. What about access to process, people, and ideas?

At that 2014 Quantified Self Public Health Symposium we were happy to have Ian Eslick join us and give a short talk about personal data and the scientific process. Access to the methods of science and the scientific process is an important piece of the puzzle, especially as personal data become easily captured and more readily understood. Too often, the world of science and research is help up on a pedestal, out of reach for individuals struggling to understand themselves. In this talk, Ian touches on his personal journey of self-experimentation and how access to the “tools of science” can be highly impactful, especially for those battling chronic conditions.

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How to Represent a Year in Numbers

As the calendar turns over to a new year, it’s useful to look back and see what the last 365 days have been all about. Looking back is always easier when you have something to look back on, and, no surprise here, self-tracking is a great help for trying to figure out how things went. That’s what makes this time of year so interesting for someone like myself. I spend a good deal of my time trying to track down real-world examples of people using personal data to explore their lives. Sometimes it’s easy, and sometimes it’s hard finding people willing to expose themselves and their data. However, when late December rolls around, I perk up because this is the time for those yearly reviews.

I’ve spent the last few weeks gathering up some great examples from individuals from all over the world. I hope the following examples inspire you to track something new in 2015 and maybe share it with the QS community in person at a local meetup, at our QS15 Global Conference, or in our social channels. Okay, let’s dive in!

My Year 2014 in Numbers #QuantifiedSelf by Ragnar Heil. A brief, but fun post detailing a year of music, travel, and location checkins.

2014: A Year in Review with iPhone Pedometer Data by Geoffrey Litt. I really enjoyed this very thorough exploration of a year’s worth of pedometer data gathered from the Argus app (iOS). Not satisfied with just looking at his total step count for the year, Geoffrey ran a series of data explorations. Among my favorite, his visualization of his daily rhythms:

GeoffreyLit_StepHours

2014 in Numbers – My Life Behind the Command Line by Quincy Larson. Work, wellness (sleep and running) and reading – it’s all here. I like the idea of tracking what you’ve read by writing one tweet per book.

2014, Quantified by Sarah Gregory. Sarah does an amazing job of capturing and showcasing her 2014 activities in this beautifully simple post. With a balance of pure quantitative information and qualitative insights I found this review especially compelling. (It was also nice to see that she used our How to Download Your Fitbit Data tutorial.)

2014 in Numbers by Donald Noble. Speaking of our Fitbit data download tutorial, here’s a short post about a year’s worth of steps – 4.15 million steps to be precise.

Three Years of Running Data: 1,153km with Nike+ and Mind by Todd Green. As you can see from the title, this post details three years of running, but as a runner myself I always like peeking into other runner’s data. (Todd also has a fantastic post from early 2014 about tracking every penny he spent in 2013.)

Food, Glorious Food by Peter Chambers. A fun post detailing what Peter and his family ate for dinner nearly every day of 2014. One juicy bit – the most common meal? Chili – Peter’s favorite!

2014 in Numbers by Jill Homer. With the help of her Strava app, Jill details her cycling and running from 2014. Click for the numbers, stay for the gorgeous photos.

I wrote every day in 2014: Here’s an #infographic by Jamie Todd Rubin. It’s great fun following Jaime’s blog. He’s relentless on his journey of daily writing (and is quite the active Fitbit user as well). What was 2014 like for his writing? Over 500,000 words – almost enough to take on Tolstoy’s War and Peace. Plus, the visualization is great (click through for the full version):

JamieTR_Writing

2014 Stats by Dan Goldin. Amazing data gathered from a self-designed Google spreadsheet that includes mood, sleep, food, and drink.

Tracking My Life in 2014 by Mike Shea. Mike tracks his life using his own custom designed “Lifetracker app.” This includes his rating on six aspects of his life, daily activities, media, and location. In this post he turns his 8,400 rows of data into elegant visualizations and interesting analysis:

MikeShea_2014

A Year in Review of Personal Data, Should be, well, Personal. By Chris Dancy. As always, Chris has an interesting and entertaining post about his 2014 data and how it compares to 2013.

Tiny Preview By Lillian Karabaic. If her previous work is any indication this year’s review is going to be great. Keep in mind this is just a place holder until the full post is up.

Why #DIYPS N=1 data is significant (and #DIYPS is a year old!) by Dana Lewis. Along with her co-investigator, Scott Leibrand, Dana has been on a journey to better control, understand, and generate knowledge about her type 1 diabetes through augmenting CGM data, devices, and alerts. What started as project to make alarms more clear and useful has morphed into a full on DIY closed loop pancreas. In this post, Dana explores what they’ve learned over the last year of data collection. Truly inspiring work:

My Quantified Self Lessons Learned in 2014 by Paul LaFontaine. In this post Paul recounts what he’s learned from his various QS experiments during 2014, with a focus on stress and hear rate variability. Make sure to also take a peak at his 2014 Review and Gear Review.

2014 Year in Webcam and Screenshots by Stan James. We’ve featured Stan and his great LifeSlice project here on QuantifiedSelf.com before. It’s an ingenious little lifelogging application that tracks your computer use through webcam shots, self-assessments, and screenshots. Check out this post to see a fun representation of his data.

2014 by Kyle McDonald. A very interesting diary of a year.

What 2439 Reports Taught Me by Sam Bew. We highlighted this great post in our What We’re Reading a few weeks ago, but it deserves another mention here. Sam analyzes the data collected from using the Reporter iOS app and writes about what he learned.

2014 Personal Annual Report by Jehiah Czebotar. Coffee, travel, Citi bike trips, software development, laptop battery life, and webcam shots – all included in this amazing page. Presented without narrative or explanation, but meaningful nonetheless. The coffee consumption visualization is not to be missed (click through for the interactive version):JC_Coffee2

2014: My Year in Review by Sachin Monga. A mix of quantitative and qualitative data from Sachin.

My Q4 2014 Data Review by Brandon Corbin. While not a full “year in review” here, I still found this post compelling. Brandon created his own life tracking application, Nomie, and then crunched the numbers from the 60 different things he is tracking. Some great examples of learning from personal data in here.

20140101 – 20141231 (2014). Noah Kalina started taking a photo of himself on January 11, 2000. On the 15th anniversary of his “everyday” project he published his 2014 photos.

Reading
When I was spending late nights searching for variations on “2014”+”data”+”my year in review” I stumbled upon quite a few posts detailing reading stats. Here’s a good selection of what I can only assume is a big genre:

2014 Reading Stats and Data Sheets by Kelly Jensen. A great place to start if you want to track your own reading in 2015. Kelly provides links to three excellent spreadsheet examples.

My Year in Reading by Jon Page. Short and to the point, but a great exploration of format, genre, and authors.

My Year in Reading: 2014 by Annabel Smith.

My Year in Books, Unnecessarily Charted by Jane Bryony Rawson.

Well, that it for now. Special thanks to Beau Gunderson, Steven JonasNicholas Felton (and many others) for sending in links and tips on where to find many of the above mentioned work. If you have a data-driven year in review please reach our via email or twitter and we’ll add it to the list!

If you’re interested in learning about how people generate meaning from their own personal data we invite you to join us for our QS15 Global Conference. It’s a great place to share your experience, learn from others, and get inspired by leading experts in the growing Quantified Self Community. Early bird tickets are on sale. We hope to see you there.

If you’ve made it this far here’s a fun treat: Warby Parker made neat little tool you can use to generate a silly personal annual report.

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Fabio Ricardo dos Santos on Using Relationship Data to Navigate a Chaotic Life

I’m fascinated by self-tracking projects that focus on things that are hard to quantify.

Such is the case here. Fabio Ricardo dos Santos is gregarious and likes to be around people. A lot of people. But he had a nagging sense that something was out of balance.

To better understand why, he began to track his relationships and interactions. He soon found that out of the people that he knows, only about 14% are what he considered to be important relationships and that they made up 34% of his interactions. He felt that this number was too low and it spurred him to spend more time with that important 14%.

But he didn’t just track his time with people and the number of interactions. He expanded his system to include the quality of his relationships and interactions. He found that this made him focus on face-to-face interactions and video chats over emails and texts.

The other side of this, though, is that when you have a system where you rate and rank your relationships, how does it not seem like you are rating people? What are the implications of doing so?

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Meetups This Week

There are an incredible 12 QS meetups getting together this week in seven different countries.

Both Toronto and St. Louis will discuss how to use self-tracking tools to keep New Year’s resolutions. In Indianapolis, people will talk about their recently acquired tracking devices from the holidays. Geneva will be doing a review of 2014, where attendees will mention their pick for the most interesting QS thing that occurred. Budapest will feature a couple toolmaker talks in addition to their show&tells, and Portland will be getting together for a workgroup session to make progress on their personal data projects.

QS meetups take many different forms. To see what the meetup in your area is like, 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!

If you organize a QS meetup, please post pictures of your event to the Meetup website. We love seeing them. Have a good week!

Monday, January 19
Oslo, Norway
Toronto, Canada

Tuesday, January 20
Miami, Florida
St. Louis, Missouri

Wednesday, January 21
Budapest, Hungary
Dallas/Fort Worth
Geneva, Switzerland
Madrid, Spain

Thursday, January 22
Grand Rapids, Michigan
Ljubljana, Slovenia
Portland, Oregon

Saturday, January 24
Indianapolis, Indiana

Here’s an image from last week’s meetups. The group in Dallas got together for an informal chat over dinner and one of the members tried out an HEG (hemoencephalography) headband, a device that measures blood flow in the prefrontal cortex.

DFWMeetup

 

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What We Are Reading

Enjoy these articles, examples, and visualizations!

Articles

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)

Show&Tell

monkeyglandin_CaffeineSleep 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?”

 

ShrivatsIyer_BooksFour 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.

Visualizations

ChandlerAbraham_MessagesPretty 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.

 

HR_proposal2Heart 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

Fits & Starts
File format for centralized storage of Quantified Self data
Embedding/Sending data to Website
Data Collection & Analysis

 

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QS Access: New Data Privacy Legislation on the Horizon

“If we’re going to be connected, then we need to be protected. As Americans, we shouldn’t have to forfeit our basic privacy when we go online to do our business”.  - U.S. President Barak Obama

In a speech this week at the the Federal Trade Commission President Obama spoke about new measures he hopes to bring forward in 2015 focused on consumer and student data privacy. In his speech he outlined four key focus areas his administration will be working on in 2015:

  • Providing a federal standard for reporting data breaches. This will establish a 30-day notification requirement for companies if customer information has been exposed.
  • Signing up major financial institutions to agree to release credit score information to their customers free of charge.
  • Protection of data gathered by companies operating in the education sector. Companies will be prevented from selling student data to third parties.
  • The introduction of a Consumer Privacy Bill of Rights.

It remains to be seen how these initiatives will affect the companies currently collecting and storing personal self-tracking information. We’ll follow along closely in our Access channel so stay tuned.

Speech Transcript

Fact Sheet: Safeguarding American Consumers & Families

Quantified Self Labs is dedicated to the idea that data access matters. Moving forward, we’re going to be exploring different aspects of how data access affects our personal and public lives. Stay tuned to our QS Access channel for more news, thoughts, and insights.

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