Beth Martin: Healing & Change Through Quantification

In 2013 Beth Martin was dealing with a failing startup, starting a new venture and working so much she moved her office into her bedroom to limit the time between waking and starting work. After a series of additional changes led her to near breakdown she decided to take six months off to rewrite her life. In this talk, presented at the Berlin QS meetup group, Beth describes the series of self-imposed challenges she created for herself and what she learned while tracking them and their impact on her life.

Posted in Videos | Tagged , , , | Leave a comment

Meetups This Week

There are five Quantified Self meetups occurring this week in the United States and England! The original Quantified Self group, Bay Area, will be convening in San Francisco for a lovely slate of Show&Tell talks on dating, diabetes, and more.

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, February 2
Bay Area, California
Manchester, England
Oxford, England

Tuesday, February 3
Reno, Nevada

Wednesday, February 4
Pittsburgh, Pennsylvania

Here are some photos from last week’s Vienna’s unconference-style meetup and Los Angeles!
Vienna1 QSLA2QSLA3 QSLA1

 

Posted in Meetups | Tagged , | Leave a comment

What We Are Reading

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!

Articles
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.)

Mindrider

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).

Show&Tells
RyanQuan_sleep-cycle-analysis-03
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.

Visualizations

EricBoam_Resume
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.

JawboneWeightLoss
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.

ER_RunRide2013-14
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

From the Forum
Jawbone Up
How to find all major volunteer bioscience projects I can partake in?
Bluetooth pulse oximeters…
Best Heart Rate Monitor that syncs with Withings Ecosystem

Posted in What We're Reading | Tagged , , , , , , , | Leave a comment

QS Access: Precision, Patients, and Participation

This morning President Barack Obama announced a new Precision Medicine Initiative, a key $215 million piece of the proposed 2016 budget. Much has been written since last week’s State of the Union, when this initiative was first mentioned by President Obama. In brief, the initiative is an investment in new programs and funding initiatives at major government bodies that influence the current and future health of all Americans, including the National Institutes of Health (NIH), the Food and Drug Administration (FDA), and the Office of the National Coordinator for Health Information Technology (ONC). These programs will focus on developing “a new model of patient-powered research that promises to accelerate biomedical discoveries and provide clinicians with new tools, knowledge, and therapies to select which treatments will work best for which patients.”

There is a lot of information being circulated about this new initiative, and we’ve collected some links below, but we’d like to highlight something directly related to our interests in self-tracking data, personal data access, and new models of participatory research. In this morning’s announcement President Obama mentioned a long-term goal of creating a participatory research cohort comprised of 1 million volunteers who will be called upon to share personal medical record data, genetic samples, biological samples, and diet and lifestyle information. This is truly an ambitious goal and we are happy to see the President take care to mention the importance of including patients and the individuals who collect this data in the decision making and research process. For example, here is the description of this specific program from the NIH Precision Medicine Infographic

NIH_PM_Participation

Here at QS Labs, we’re dedicated to helping create and grow a culture that enables everyone to generate personal meaning from their personal data. Sharing, participation, and exploring new models of discovery are a core themes we’re exploring as part of our QS Access work. We’ll be following this initiative as it moves from today’s announcement to tomorrow’s reality. Be sure to stay tuned to our QS Access Channel for more updates as we learn more.

Learn more about the Precision Medicine Initiative
NIH mini site describing the initiative
White House Blog: The Precision Medicine Initiative: Data-Driven Treatments as Unique as Your Own Body
FACT SHEET: President Obama’s Precision Medicine Initiative
A New Initiative on Precision Medicine by Francis Collins and Harold Varmus (New England Journal of Medicine).

Posted in QS Access | Tagged , , , , , , , | Leave a comment

Counting Money

Yesterday was the first day in a month that I handled cash. For weeks everything I’ve purchased and paid for has been handled by digital means. Debit cards, direct debits and deposits, internet purchases – it’s all 1′s and 0′s flowing through the tubes, and it’s makes my life very easy. However, now that the flow of money in and out of my life is easier, I have to find new ways of being aware of what’s happening to the money. I’ve gathered up a few examples of QS projects, show&tell talks and articles related to money – please feel free to share your own favorites. -Ernesto

Show&Tell Videos

Amaan Penang: Making Data-Driven Financial Decisions
Amaan Penang was faced with a life change when he moved from Texas to California to start a new job. While preparing for the move he started to examine his financial health and was surprised by what he didn’t understand about his spending and income. Using the popular financial tracking software, Mint, he started to examine his historical spending. In this talk Amaaan explains what he learned and how he was surprised to find out how this data opened up the doors to exploration and better financial health.

Natty Hoffman: The Enlightened Consumer
Natty had a large amount of financial data, over 14 years of expenses and spending, that she was accessing from credit card and bank statements. Because of her work as a consultant she was experiences with understanding and reconciling her various accounts and reimbursements. It wasn’t until attending a QS meetup in Boston that she realized that there was more to her data than just historical financial documents,

“I didn’t really think much about this data until I went to a Quantified Self meetup a few months ago. And then I said to myself ‘You know, I have some pretty interesting data about myself as a consumer and I wonder what I’m going to find out.”

Natty started exploring her data by looking back at the last two years to better understand the where her money was going based on a broad categorization scheme. But, she didn’t stop there. She went on to explore exactly where she was spending her money and found that she was a customer of over 300 different businesses over the two years she examined. Intrigued by the the companies she frequented she went deeper and started to see how she did as a consumer and if her spending behavior matched her personal ideals.

Matic Bitenc: Manual Finance Tracking
Outside the US there aren’t many good options for automatically tracking personal finances. Matic and his partners created Toshl Finance, an application for manually tracking how he was spending his money. In this talk Matic describes what he learned about his expenses and lifestyle by using a simple tag-based system and easy to understand visualizations.

Examples of Personal Finance Tracking

Tracking, Classifying, and Comparing Expenses by Karsten W.
We featured this very interesting tracking project in 2012 when Karsten embarked on a experiment to track his spending via a simple Twitter tool. Not satisfied with just tracking, he also categorized and compared his spending habits to what a typical person in his country (Germany) spent in different categories.

How I track my personal finances and Keeping (financial) score with Ledger by Sacha Chua.
Two great posts by our QS Toronto co-organizer, Sacha Chua. In the first she describes how she sets up understanding her financial life, and in the second she describes her tracking methodology.

I Tracked Every Penny I Spent For One Year. Here’s What I Learnt by Todd Green.
As the title says, Todd tracked his spending for an entire year. In this post he describes the process and the top 10 lessons he learned.

Articles of Note:

The Quantified Self Movement Reaches Personal Finance
Key Quote: “Personal finance tools as they evolve will take this technology much farther. GPS-based navigational systems have both improved and become more ubiquitous as raw data have become more available and the cost for both devices and services has dropped. So too will personal finance apps begin to follow us around. They’ll live in our phones or on our wrists, pulling in real-time data to help us take control of our own short-term liquidity and solvency needs and long-term retirement goals.”

What Health and Finance Can Learn From the Quantified Self Movement and Each Other.
Key Quote: “Few domains of life are as quantified as your financial self — you have your credit score, savings and checking balances, 401Ks, stocks, bonds, funds and more aided by countless apps, reports and plans provided by banks, employers and financial advisors all available online, on the phone, in person and at your local ATM.”

Banking on you — how wearable tech could change finance.
Key Quote: “Historically, banks have been some of the richest repositories of data — but also the least likely to do something innovative with it. This is partly due to regulation, but mostly due to a self-limiting mindset prevailing in the banking industry. Till now, consumers have accepted this status quo, but not for much longer. As they find their ‘quantified selves’ no doubt their demand for insights into their finances will increase.”

Financial Wearables – Part 1: Can high-tech wearables solve underserved people’s financial problems?
Key Quote: “Managing money in cash is time consuming—time to get cash, calculate it, record your every transaction. Banks do most of those actions, but do not teach you how to spend better and save money at the same time. The potential power of wearables is not in presenting you with “transactional information” about how many steps you took on a given day, but rather in showing how you can improve those steps over time with alerts, recommendations and visual elements. Banks could use the “wearables” power to incentivize users to better their financial health, deliver liquidity management tools and foster strong banking relationships and maximizing customers’ assets instead of their fees. It not only helps individuals but the bank as well.”

YOUR MONEY-Financial obsessives track every penny, every minute
Key Quote: “Australian academics Ken Cheng and Megan Oaten of Sydney’s Macquarie University once had volunteers write down every single purchase for four months, which led to marked improvement in their financial lives. They also found that positive financial habits started bleeding into other areas, with the volunteers improving their behavior in everything from house cleaning to exercising.”

‘Quantified Self’ Movement Now Lets You Track Your Money Too
Key Quote: “Cozy Cloud co-founder Frank Rousseau was originally inspired to invent the self-hostable personal cloud platform because he wanted an open source alternative to Mint.com, he told us earlier this year. But the hard part is that most banks don’t provide APIs to help users get their data out of the banks, according to the project website. To do this, Open Bank Manager is relying on a tool called Weboob (WeB Outside Of Browser) to scape data from banking sites.”

ToolsNot a complete list, so please add more in the comments and we’ll update here
Mint
Money, by Jumsoft
Personal Capital
Expensify
DollarBird
Spending Tracker
Checkbook
Also make sure to check out the long list of personal finance apps people are talking about on Product Hunt

Additional Reading
Why Wesabe failed: Marc Hedlund’s Challenge
An interesting look back at how another personal finance tool failed in the face of competition from Mint.

How can new interactions with digital money make us more aware of our spending? Chris Woebken talks about this design experiments here.

Posted in Discussions | Tagged , , , , , , , | Leave a comment

QS Access: Data Donation Part 1

New sensors are peeking into previously invisible or hard to understand human behaviors and information. This has led to many researchers and organizations developing an interest in exploring and learning from the increasing amount of personal self-tracking data being produced by self-trackers. Even though individuals are producing more and more personal data that could possibly provide insights into health and wellness, access to that data remains a hurdle. Over the last few years a few different projects, companies, and research studies have launched to tackle this data access issue. As an introduction to this area, we’ve put together a short list of three interesting projects that involve donating personal data for broader use.

DataDonors.org
Developed and administed by the WikiLife foundation, the DataDonors platform allows individuals to upload and donate various forms of self-report and Quantified Self data. Data is currently available to the public at no cost in an aggregated format (JSON/CSV). Data types includes physical activity, diet, sleep, mood, and many others.

OpenSNP.org
OpenSNP is an online community of over 1600 individuals who’ve chosen to upload and publicly share their direct-to-consumer genetic testing results ( 23andMe, deCODEme or FamilyTreeDNA) . Genotype and phenotype data is freely available to the public.

Open Paths
Open Paths is an Android and iOS geolocation data collection tool developed by the New York Times R&D Lab. It periodically collects, transmits, and stores your geolocation in a secure database. The data is available to users via an API and data export functions. Additionally, users can grant access to their data to researchers who have submitted projects.

We’ll be expanding this list in the coming weeks with additional companies, projects, and research studies that involve personal self-tracking data donation. If you have one to share comment here or get in touch.

Posted in QS Access | Tagged , , , , , , , | Leave a comment

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.

Posted in Videos | Tagged , , , , , , | Leave a comment

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

 

Posted in Meetups | Tagged , | Leave a comment

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)

Posted in What We're Reading | Tagged , , , , , , | Leave a comment

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.

 

 

 

 

 

Posted in QS Access | Tagged , , , , , , | Leave a comment