Laila Zemrani: Training for Strength or Endurance?

While it is clear that exercise is beneficial, how does one decide what to do to get and stay fit? When Laila Zemrani surveyed people at the gym, she found that a majority don’t decide at all. Sixty percent didn’t know why they were doing a particular exercise. And of those, 50% admitted to merely copying whatever their neighbor was doing.

Laila spoke recently at a QS meetup in Boston about how she tried to be more intentional in her choice in exercise. In reviewing the number of available exercises, she was able to put them into two buckets: strength and endurance. She decided to track the effectiveness of each training regimen by focusing on a single metric and watching its progress. For strength, she focused on body fat ratio. For endurance, she looked out how long it took her to run the same distance. She then alternated her training every three months or so, focusing on one or the other.

Laila Zemrani speaking at QS Boston

Laila Zemrani speaking at QS Boston

Here’s what she found. When she focused on strength training, her body fat ratio improved. For instance, in one three month period it went from 29% to 25%. This type of improvement repeated itself a number of times. However, when she focused on endurance, she did not see improvements in the time it took her to run a certain distance.

Using a Fitbit Aria, Laila tracked body fat while alternating training regimens.

Laila tracked body fat with a Fitbit Aria scale.

It’s hard to know what conclusion to draw from these results. Are these the right metrics for assessing performance? What does it mean to respond more to strength than endurance exercise? However, the question of why Laila seemingly responds better to strength-based exercises may be found in her genetics. She used a DNA test from 23andMe and the results suggested that she shows a propensity toward building fast-twitch fibers which allow for better performance at explosive activities, such as sprinting or weight-lifting. On the flip side, people who are more proficient at building slow-twitch fibers tend to do better at endurance-type activities such as running long distance. Everyone has a combination of the two types of muscle fiber, but the ratio seems to be correlated with performance, depending on the type of activity.

Screenshot from Laila's 23andMe account.

Screenshot from Laila’s 23andMe account.

With these results, Laila decided it made sense for her to focus on strength-building exercises, since it seems that her body was built for that type of activity. Laila feels that having this information is allowing her to personalize her regimen and be more intentional about how she exercises, rather than be too influenced by the latest fads in fitness.

It can be debated whether it makes sense to focus on strength as opposed to endurance, depending on which one you see progress in. For Laila, the appearance of progress is important psychologically, in that it is easier to motivate herself if she sees improvement. There could be a downside to appearance of quick improvement, though. Ralph Pethica also uses genetic data to inform his training. He is the opposite of Laila in that his body is better suited for endurance exercise. What he finds, though, is that he improves and adapts too quickly and sees his performance plateau. To overcome this, he found that switching between steady-state training sessions and high-intensity intervals minimized the time he spent plateaued.

Training with knowledge of your genetic background is still a nascent practice. It’s still unclear how this information can and should be used. Useful ways to take advantage of this genetic information is still being tested and developed, but progress could be hastened if more people knew if they had more slow-twitch or fast-twitch muscle fiber. If this awareness is increased, it could lead to better strategies to get more out of exercise and reduce frustration and, hopefully, abandonment of the gym.

You can watch Laila’s entire Show&Tell presentation that she gave at a QS Boston meetup. You can follow up with Ralph’s Show&Tell from the QS Europe conference.

Tools used:
Fitbit Aria

QS17 Tickets are Available

Our next conference is June 17-18 in lovely Amsterdam. It’s a perfect event for seeing the latest self-experiments, debating the most interesting topics in personal data, and meeting the most fascinating people in the Quantified Self community. There are only a few early-bird discount tickets left. We can’t wait to see you there.

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Stefano Schiavon: Using Data to Understand Personal Comfort

Stefano Schiavon is an assistant professor and researcher interested in sustainable building design. As he told us at last month’s Quantified Self meetup in Berkeley, California, “I am Italian. I love architecture. And I think buildings are beautiful.”

One goal of building design is to increase individual comfort. However, this poses a problem. Everyone is different. For instance, what should the temperature be set at? There is no one temperature that is comfortable for everyone. It doesn’t work to try find a temperature that is pleasant to the largest number of people. As Stefano puts it, it is like going around and measuring everyone’s foot to get an average, say 9, and then dictating that everyone wear size 9 shoes to the office.

So how does this connect with Quantified Self? Stefano and his colleagues have embarked on a series of studies to better understand people’s individual preferences for their environments and they are doing it with QS tools. The first study was fairly simple. They tracked the ambient temperature and air quality of the person’s surroundings and used an app for feedback on whether the environment was “acceptable” or not. Carbon dioxide and temperature measurements were taken throughout the day, while the person was in the car, at work, the restaurant, etc.

4_Stefano Schiavon Personal Comfort Quantified Self MeetUp.007
Stefano and his colleagues noticed a couple things. One is that there was higher exposure to CO2 in air conditioned rooms as opposed to naturally ventilated rooms. While Stefano says that this CO2 level is not a concern in of itself, it correlates with other pollutants, such as, airborne transmitted diseases (e.g., influenza).

4_Stefano Schiavon Personal Comfort Quantified Self MeetUp.008

Despite these data, Stefano and his colleagues found that just recording the environment gave him a limited ability to predict a person’s comfort. He is hoping, and the focus of his next study, is that by getting a person’s QS data (heart rate and body temperature), this predication ability will improve, making it easier to personalize a space’s comfort for each individual.

4_Stefano Schiavon Personal Comfort Quantified Self MeetUp.010For Stefano, all of this is in support of a larger cause, climate change. He was saddened to discover that nearly 40% of greenhouse emissions come from buildings. He hopes that by building better models for personal comfort by using QS tools, he can help people enjoy their environments more, while minimizing the environmental impact.

You can see the entire video of his talk at his QS project page.

Here are links to some of Stefano’s papers:

Get your tickets for QS17

Our next conference is June 17-18 in lovely Amsterdam. It’s a perfect event for seeing the latest self-experiments, debating the most interesting topics in personal data, and meeting the most fascinating people in the Quantified Self community. There are only a few early-bird discount tickets left. We can’t wait to see you there.

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College Performance by Tiffany Qi


Tiffany’s calendar

I think I spent more time flailing than planning in college. Though I’m not sure, because I don’t have the data. Tiffany Qi does, though. During her four years of undergrad, she meticulously tracked her time, putting it in one of several categories, “planning” being one of them. Now that she has her degree in Business Administration, she spent some time analyzing the wealth of data she collected as an undergrad. For this talk, given at the a Quantified Self meetup last month in Berkeley, California, she focused on the relationship (or lack thereof) between how she spent her time and her academic performance.

In particular, she explored the following questions:

  • Did her commitment to her studies wane over time?
  • How much did time spent studying matter for her final grade?
  • Did the amount of time spent on fun help or hinder her grades?
  • Did having a job or other job-like responsibilities lower her grades?

You can watch the full video at Tiffany’s QS project page. For a more detailed look at this project, Tiffany wrote about it here and here.

Tools used:
-Google Calendar
-CalenTools (Tiffany’s custom tool that she made for this project)

Get your tickets for QS17

Our next conference is June 17-18 in lovely Amsterdam. It’s a perfect event for seeing the latest self-experiments, debating the most interesting topics in personal data, and meeting the most fascinating people in the Quantified Self community. There are only a few early-bird discount tickets left. We can’t wait to see you there.

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What We Are Reading

Even though our work at Quantified Self is not ostensibly political, we have been thinking lately about its relevance to the tumultuous times in U.S. politics. Although there is uncertainty and fear, we, like many others, feel activated to make a difference as individuals, more than we did before.

One of my fundamental beliefs about Quantified Self practices is that it leads people to be better versions of themselves. I don’t mean this in the bigger, stronger, or faster sense. It helps people become active agents in their lives. To be more curious and challenge certainty in themselves and others. In navigating this uncertain time and figuring out how to make a personal contribution, communities will play a larger role in people’s lives. It’s important to me, at least, that we are a community that encourages thoughtfulness and thoroughness in reasoning and perspective. I don’t know exactly what our role will be, but we stand in solidarity with those who fight for a better world and defend against capriciousness, avarice, and false confidence. In that spirit, my colleague Erica has put together a beautiful, short video of her experience at the Women’s March on D.C.

I hope you enjoy these articles. Some are a welcome respite. Others may help with understanding the current situation. If you have any suggestions for what we can do to help or if you read anything that we should include in a future WWAR, send it my way at



Algorithmic Life by Massimo Mazzotti. Trendy words become objects of derision. When a word with a range of meanings is overused, it becomes ever more ambiguous, as each discrepant situation through which it passes rubs away some of its precision, until the sound of the word does nothing more than evoke vague memories of where it’s been. Words that have been with us through many struggles, like “justice” or “pride,” acquire the opacity of nearly universal significance. But new minted words, without historical weight— people may just start to laugh them. The word algorithm has begun to suffer this fate. This sensitive essay by historian of science Massimo Mazzotti argues that the semantic confusion of “algorithm” is an invitation to revise our assumptions about people and machines. -Gary

Why Medical Advice Seems to Change So Frequently by Aaron E. Carroll. Nutritional recommendations are a tricky business. Some wonder why scientists can’t get their story straight. Sometimes the issue is that a perceived effect disappears when a more rigorous experiment is done. Another issue is that some people will benefit from an intervention, but it is then proclaimed that all people will benefit. There’s also the problem of studies with negative results being hidden from view. -Steven

Tracking Physiomes and Activity Using Wearable Biosensors Reveals Useful Health-Related Information, by Xiao Li, Jessilyn Dunn, and Denis Salins. This article from PLOS-Bio is a top contender for “QS Paper of the Year.” True, this award was just invented, and the year has barely started. Still, I invite you to download it and see if you can find reasons to disagree. Based on nearly two years of extremely detailed self-tracking by one 58-year old participant, and strengthened by additional group research, the paper makes substantive new discoveries and demonstrates the power of accessible tools for self-measurement. The participant is Mike Snyder, principle investigator in the Stanford lab where the authors work. (Aside from many other interesting things about the paper, it’s an important example of participatory research methods.) Back in 2011, an individual self-experimenter, John de Souza, gave a talk at our QS conference showing that he could predict sickness – before symptoms were felt – by looking at elevation of peak heart rate during exercise over a well established baseline average. Li, Dunn, and Salins’ paper contains a similar result based on elevation of resting heart rate. The data supporting this conclusion is very rich, including both self-reported symptoms and elevated hs-CRP, a marker of inflamation. There is much too much additional interesting material to quickly summarize; thankfully, PLOS-Bio is open access, so have at it. -Gary

Most People Are Bad at Arguing. These 2 Techniques Will Make You Better by Brian Resnick. Something that I see play out on Facebook currently is the futility of arguing with those that we disagree with. It’s not often the case that this does anything to change minds. This article looks at how empathy and listening can make a difference. -Steven

Cortisol and Politics: Variance in Voting Behavior is Predicted by Baseline Cortisol Levels, by Jeffrey A. French, et al. While I don’t have super high confidence the conclusions from this paper published in 2014 are going to hold up, the connection between variations in stress tolerance and participation in politics is very interesting, and more accessible measurement tools are going to allow a much closer look than we’ve ever had before. An intuitive understanding of how to induce and relieve stress has been part of politician’s toolkit forever, but now more than ever we need some kind of self-understanding of our own physiological patterns of response, in order to be able to reflect better on what’s happening around us. -Gary

The FDA Is Cracking Down On Rogue Genetic Engineers. Up until this point DIY biohacking has largely operated without government oversight. As this technology moves out of niche communities and becomes commercialized, there are concerns over whether the FDA will include DIY biology enthusiasts in the rulemaking process. -Steven

Show & Tell

The Year 2016 by Lillian Karabaic. Lillian releases her 9th annual report, with entertaining visualizations, whimsical metrics (e.g., tacos consumed), and a light-hearted, but not to be taken lightly, study of burnout from a new job. -Steven

Introducing BobAPI — A Personal API to Collect and Share All of My Life Data by Bob Troia. I missed this when he originally released it, but Bob created a unified data store that allows him to have control and ownership of his data and better equip himself to contribute to citizen science. I hope this proves to be a model that others follow. – Steven

A College Student’s Individual Analysis of Productivity of Four Years by Tiffany Qi. Tiffany recently graduated from UC Berkeley. During her four years of undergrad study, she tracked her time and productivity. In this analysis, she looks at how how her time spent affected her grades. -Steven

Data Visualizations


One Angry Bird: Emotional Arcs of the past Ten U.S. Presidential Inaugural Addresses. This analysis looks at facial expressions used by the last ten presidents as they give their inaugural addresses. Both the visualizations and method of analysis are novel. -Steven Often Do I Look at the Time? by Ravi Mistry. This is a of a visualization of a novel metric: “how often one looks at the time.” I’m impressed by the discipline required to pull this off. -Steven


AccidentalArt (1)Accidental aRt. This is a twitter feed for R visualizations that go “beautifully wrong.” My personal title for this beautiful work of accidental art is: “Causation is not correlation.” -Gary

QS17 Conference

QS17SidebarLogoOur next conference is June 17-18 in lovely Amsterdam. It’s a perfect event for seeing the latest self-experiments, debating the most interesting topics in personal data, and meeting the most fascinating people in the Quantified Self community. There are only a few early-bird discount tickets left. We can’t wait to see you there.

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Meetups This Week in Switzerland and Ireland

It’s 2017 and we’re looking forward to a new year of fun and informative Quantified Self meetups. This week brings the first of the bunch with Zürich and Dublin.  Zürich‘s meeting will feature a presentation on the current and future impact of the Quantified Self movement on Swiss society. Dublin will feature great talks on how to use blood testing to track and improve various biomarkers.

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 are a QS Organizer and want some ideas for your next meetup, check out the myriad of meetup formats that other QS organizers are using here.

Tuesday, January 10
Zürich, Switzerland

Friday, January 13
Dublin, Ireland

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What We Are Reading

It’s a new year, and we are starting it off with a collection of articles that we’ve been collecting for the last couple of months. I hope you find them as interesting as we did. -Steven


Making Statistics Matter: Using Self-data to Improve Statistics Learning by Jeffrey L. Thayne. Can Quantified Self projects solve an ongoing problem in teaching statistics? This doctoral dissertation supervised by Victor Lee, a long time participant in our Quantified Self Public Health symposia, argues that it can. The reason QS can help is simple: in QS practices, statistics become personally relevant. As Thayne writes:

[A]n essential feature of effective statistics instruction [is] a relevant, immediately available context of application, wherein learners feel that they are taking part in an ongoing inquiry process in which statistics is being used as a tool for illuminating something new and important about their world.

What I found especially interesting about this research, which used qualitative methods to explore student’s interest and involvement in their statistics learning, was that the use of self-collected data was not powerful because it appealed to the student’s vanity, but because it was familiar and had contextual meaning. Just as professionals who use statistical methods benefit from understanding where the data comes from and what it is for, students who can situate their practice in a rich context find it easier to master new methods. -Gary

On Progress and Historical Change by Ada Palmer. Historian and science fiction author Ada Palmer’s lucid essay on the idea of historical progress is great to read in light of the never-dying hope among the makers of self-tracking tools that there can be a formula for positive change. I sometimes tire out my colleagues opposing this idea, and I know it seems odd that here at Quantified Self we spend every day supporting people trying to figure out how to use technology for change while at the same time not believing that definite techniques for inducing such change can exist. Isn’t that a contradiction? In contrast to my usual philosophical abstractions and pedantic references to the history of behavioral psychology, Palmer tells the story of where our idea of progress comes from, and offers a fascinating account of how events can be simultaneously free and determined, based on the DIY historical simulation machine she builds every year with her students. -Gary

How a Guy From A Montana Trailer Park Overturned 150 Years of Biology by Ed Yong. One of my favorite stories in citizen science is how Beatrix Potter (of Peter Rabbit fame) was an early and ridiculed proponent of the idea that lichen was a symbiotic fusion of a fungi and an algae. The need for the term “symbiosis” arose from this discovery (credited to Swiss botanist Simon Schwendener). This article follows the humble beginnings of Toby Spribille and the process for how he determined that the theory that lichen is composed of two organisms is wrong. It’s actually three. -Steven

How To Do What You Want: Akrasia and Self-Binding by Daniel Reeves. I’ve been going back and reading some of Daniel Reeves’ excellent posts on the Beeminder Blog about the cluster of concepts and techniques associated with self-control, including also Smoking Sticks and Carrots and What is Willpower? -Gary

How Language Helps Erase the Tragedy of Millions of Road Deaths by Julie Sedivy. What is the difference between the words “accident” and “collision”? The word “accident” implies a lack of blame. This article explores the effects that these connotations have on our subconscious interpretation of the world. -Steven

Faster, Not Smarter: Does Caffeine Really Make You More Productive? by Alex Senemar. Alex surveys what is known about the effects of caffeine on productivity. How do you keep caffeine a boon and not a crutch. What I love about this article is that Alex finishes it with suggestions on how to run your own experiment to see caffeine’s effect on your productivity. -Steven

In Defense of Tracking Our Poop by Adam Butler. Adam makes the argument that one of the best ways to understand the health of the microbiome is to track and pay attention to your poop. How do you turn that into data? Luckily, there is a time-tested classification system that your physician should recognize called the Bristol Stool Scale. Which will help the next time you need to talk to your doctor. -Steven (courtesy of Ernesto Ramirez)

Childhood trauma leads to lifelong chronic illness — so why isn’t the medical community helping patients? by Donna Jackson Nakazawa. “Were there any childhood traumas or stressors that might have contributed to the extreme level of inflammation you’re experiencing as an adult?” Nakazawa says that this was the most important question posed to her in her adult life. From the question, she was able to untangle how her present day health issues have ties to the traumatic death of her father when she was twelve. The article shows that childhood trauma leads to a great likelihood of autoimmune disease. However, knowing about these links, one can help reduce the number of doctor visits. -Steven

Early Modern Bookkeeping and Life-Writing Revisited: Accounting for Richard Stonley, by Jason Scott-Warren. The use of numbers as an element in personal record keeping is ancient, but the account books of early modern elites hold particular interest for historians, since they seem to hold clues to the origin of today’s autobiographical habits. The great 17th century diarist Samuel Pepys kept his entries in a ledger book, and the carefully folded pages and ruled lines of the account books of bourgeois merchants and lawyers provide a dense cultural background for more famous documents (such as Benjamin Franklin’s memoirs) commonly imagined to to lie at the root of the Quantified Self. This essay from The Social History of the Archive (a special volume of the journal Past & Present) takes a close look at the account book of an obscure functionary named Richard Stonley, and shows how mistakes, repetitions, and elisions challenge the idea of the ledger book as a crucible for the modern sense of self. -Gary


How Software, Data, and a Hell of a Lot of Work Helped Me Lose 110 pounds in 25 Months by Timothy Chambers. Although he doesn’t show his data, it was interesting to read how Timothy integrated various tools into his effort to lose weight. Each tool had a role and each needed certain features to qualify. It’s a complex interaction of data sets and feedback mechanisms. I appreciated one of his points on data portability:

It was critical that my apps could speak to each other and to the cloud, not just to what companies each toolmaker had deals with. My web-based trend tools needed to talk with my scale which needed to speak to my phone. We work so hard for the health data about steps, weight, fat percentage, etc, that should be our data open to use with whatever tools we wish. Not all vendors treat it as such.


My to-do list is now public, and it’s the most useful thing I’ve done in years by Joe Reddington. For years, Joe has kept track his number of open to-do’s. In May, he experimented with making his to-do list publicly available. Now that he knows that he’s being “watched”, he is more conscientious about making his items comprehensible, and is  more motivated. As Joe puts it: “When it was [just] a list for me, it looked great; when I decided to make it public, it instantly looked very poor.” -Steven

Analysis of a Personal Public Talk by Alex Martinelli. Alex analyzes a recent talk he gave at a QS Dublin meetup, by looking at his heart rate and speaking speed. The piece has an appropriately casual tone, but he finishes each section of the analysis with a definitive statement based on the data. After looking at how fast he was talking, Alex writes as if he was consulting someone else:

Your average speech rate is 152 Words Per Minute (WPM), but an approximately constant and significant decrease can be observed, bringing you from an initial WPM of 166 to a final value of 142. The primary cause of this is the usage of increasingly longer pauses between words, secondarily reinforced by a combination of using longer words, as well as a tendency to slow down the pronunciation of words, while the talk unfolds.”

As an engineer at IBM, he’s clearly used to this at his job, but I like the idea of bringing this structure and formality to personal data analysis. -Steven

The Somniloquist by Adam Rosenberg. Adam was told by others that he talks in his sleep, so he set up a recorder to capture his “midnight monologues”. The recordings are transcribed, and in addition to being hilarious, they are an interesting insight into what the brain is doing during sleep. -Steven

My Quantified Wardrobe 2017 by Matt Manhattan. Matt analyzes his wardrobe in an effort to define his relationship with his clothes. He looks at how much of each article of clothing he has and their associated cost. But it’s the pictures of his clothes that makes this post delightful. -Steven

Data Visualizations

History Lesson by Clive Thompson. Not a visualization, but an article about the history of data visualizations. -Steven

The London Wind Map. A whimsical of visualization of where you would go if “you were pushed by the wind each day” in 2015. -Steven


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SF Bay Area Meetup Recap

On November 17th, the Bay Area and SF Meetup groups hosted QS Show&Tell talks at WeWork Mid-Market. Thank you to everybody who came and presented. We saw some brilliant talks, including one about tracking during pregnancy with data challenging common, supposedly scientific pregnancy advice, and a talk outlining a fascinating self-study of bruxism (teeth grinding) based on a DIY wearable sensor to capture muscle tension and an infrared camera filming all night. We also had a crew from National Geographic documenting the evening for a short show they are making about Quantified Self. Here are links to some of the talks!

1. Erica Forazni “Tracking Pregnancy and Baby Growth”
2. Mark Moschel, “Tracking Ketones”
3. Peter Kuhar, “Tracking my Bruxism”
4. Tahl Milburn, “Quantifying My Mental and Experiential State”

Mark your calendar for our next All Bay Area QS Meetup on January 26th, 2017 at the Wells Fargo Room located at UC Berkeley’s Haas School of Business. Just let us know when you sign up if you want to present.

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QS17: Join us June 17-18 in Amsterdam


We’ve been working for many months to organize our next Quantified Self conference, and now we’re ready to open QS17 for registration. We’re going to Amsterdam, and we hope you’ll join us.

QS17: The Quantified Self Conference - Register

This will be the fourth time we’ve held the conference in Amsterdam at our favorite venue just outside the Amsterdam city center. Those of you who have already been to a QS conference here will understand why: This calm, beautiful, and extremely well located hotel, just a short walk from the canal ring, is a perfect place to work together and learn from each other.

QS17 is what we call a “Carefully Curated Unconference.” We’ll have over 100 individual sessions, all of which are proposed and lead by conference attendees. We work closely with all the participants in advance, based on what we know of your projects, work and interests. The final program lineup is released a few days before the event. So please let us know what you’re working on when you register.

Due to the  size of the venue, attendance is strictly limited to 350 people. The first hundred people to register can sign up for €250 for the two day conference. So please don’t delay.

See you in June!

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Ahnjili Zhuparris: Menstrual Cycles, 50 Cent, and Right Swipes


“I love reading random papers about the human body.”

Ahnjili Zhuparris came across a study on the menstrual cycle’s influence on cognition and emotion and was curious to see how hormonal changes may affect her day-to-day behavior. She figured her internet use may be a convenient and easy data set to assemble and examine for this effect. Using a few chrome plugins, Ahnjili was able to see not only where she spent her time online, but how she interacted with sites like Facebook and Youtube.

Her analysis yielded some interesting patterns. She found the most distinctive behaviors occurred during the fertile window, a span of about six days in the menstrual cycle when the body is most ready for conception. Looking at her shopping data from a clothing website:

 ”I found that there was no change in the amount of money I spent or the amount of time I shopped online… but while I was most fertile, I bought more red items. In fact, it was the only time I bought red items.”

In this talk, Ahnjili shows the differences in how she browsed Facebook, swiped in Tinder, and listened to music on YouTube.

Here are a few of the tools and papers that Ahnjili cites in her talk:

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Meetups This Week

We have three great Quantified Self Meetups occurring this week. Seattle’s talk topics include failing, music listening habits, and personal analytics. Bogotá will be discussing productivity tracking. And the Tokyo group will allow everyone to give a short 3-5 min Show&Tell on what they’ve been working on.

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 are a QS Organizer and want some ideas for your next meetup, check out the myriad of meetup formats that other QS organizers are using here.

Thursday, October 6
Seattle, Washington
Bogotá, Colombia

Saturday, October 8
Tokyo, Japan

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