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.

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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.

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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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