Topic Archives: Videos

Thomas Blomseth Christiansen: Over-Instrumented Running

Some More Instrumentation Thomas Blomseth Christiansen

 

“When in doubt, add more instrumentation.”

Have you ever felt that some parts of your life should remain unquantified? Perceived quality of your poetry, or perhaps duration of arguments with your significant other? Until recently, I kept running in my ‘not to be quantified’ bucket. It was such a meditative alone time that I didn’t want to risk disturbing it through observation. I tracked the kilometers I ran and nothing more.  That changed at the finish line of a recent 50k, where I learned that my wearable had overestimated the race distance by over 8 k! I was pretty miffed, and I turned to this talk for inspiration.

Thomas inhabits the far end of the quantified running spectrum. His talk from QS17 is a fun watch, and the project page is here.

What did he do? He started out  disappointed by hitting the wall midway through a marathon. This is common enough, but Thomas’ response to running a painfully positive split was to code his own negative split plan generator, rubber band split-plan sticky notes to his arm, and set out to run at a concrete pace. His project evolved to include an olympic swimming coach, many new devices, a metronome – and ultimately mastery of the art of pacing.

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Mark Moschel: Blood Ketones During Regular Fasting

MarkMoschelWine-1Here’s proof that clarity and creativity are what make great data visualization. Mark’s illustrations show what he learned by combining mulitple-day fasts, ketone and glucose measurements and…wine.

He has generated several interesting personal insights, including some not yet published on: correlation of felt energy levels to blood ketone levels, the inverse relationship between ketones and glucose, and the ceiling effect of too-high ketones. I can’t find any publications on the wine-effect, so there may be a novel discovery in there as well. Check out Mark’s QS project page here.

I periodically become fascinated with ketosis, so the talk inspired me to revisit the topic of ketosis and prolonged fasting in women. The debate about the issue is intense, and there are relatively few publications that address women specifically. Have women in QS tried a similar experiment? What was your experience? We’ve started a forum post here on the topic.

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Kyrill Potapov: Tracking Productivity for Personal Growth

Eddie_KyrilPotapov“Once one of Eddie’s leaves wilts, that’s it. A record of my failures right there among all the green leaves.”

In a show&tell talk that is as sweet as it is clever, Kyrill asks how his grandchildren might one day learn about him through digital family heirlooms and offers this unique project as an example.

Kyrill recently acquired his grandfather’s shaving razor and was struck by the connection he felt through the evidence of ownership: the darkened areas, worn edges and other traces of use.

Reflecting on his own mostly computer-based work, Kyrill noted how little of a physical trail he leaves in the world. Could his time and productivity data leave a mark on anything? Does he have a physical object, like his grandfather’s razor, that is indirectly shaped by his toil, besides a dirty keyboard?

Kyrill explored this idea by connecting the time-tracking service RescueTime to a light placed in a box with a house plant that he named Eddie. When he spends time on things he finds personally fulfilling, like working on his PhD, the light turns on and the plant grows. When he’s caught up in other activities, the leaves yellow and die.

The arrangement adds a new dimension to his productivity data. Every couple of days, Kyrill opens the box to water the plant. This ritual provides an opportunity to take stock on how he has been using his time, based on the condition of the plant. Embodied in this living organism is his failures to stay on task and focus on what’s important. Distractions take on a new threat. Rather than just endangering his goals, they now threaten the health of Eddie.

Although Kyrill won’t be able to leave a houseplant to his descendants, it’s a worthwhile meditation on how different modes of presenting personal data can have a profound difference in the way it engages one’s emotions.

You can watch Kyrill’s talk at his QS Project page. You can read about how Kyrill  connected RescueTime to a lamp here.

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Jakob Eg Larsen: Tracking Sleep and Resting Heart Rate

JakobLarsenRHRdata

Jakob Eg Larsen has tracked his sleep and resting heart rate (RHR) for the past four years. His 7 minute talk is far better watched than read about: it’s a great illustration of data validation, longitudinal tracking, and data assisted self-awareness.

Briefly, by tracking his RHR over a long period of time, Jakob has developed an intuition for connections between his RHR and physiological state. He’s able to use the data to tune his self-awareness, but still keep a safety net when unexpected RHR elevations might portend a flu. To boot, the years of data across the Fitbit Blaze, Oura ring and Basis are one of the most extensive within-individual comparisons I can find anywhere of these devices.

You can watch the full video of Jakob’s talk at his QS Project page.

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Cantor Soule-Reeves: Fight For Your Right to Recess

Cantor

It rains a lot in Portland, Oregon. And if you’re 8 years old like Cantor, recess gets cancelled a lot. But unlike most 8-year-olds, Cantor is doing something about that.

By tracking his steps, he’s able to show that every cancelled recess takes about 600 steps out of his day. Compared to his average of ~15,000 steps a day, it might not sound like a lot, but Cantor and his mom Bethany hope it might be enough to change his elementary school’s policy for rainy-day restrictions.

We don’t typically see young children doing serious self-tracking, especially with such an altruistic (and downright cool) aim of fighting for more recess time. We have our fingers crossed, both for the school’s response and for seeing more projects like Cantor’s in the future. Check out Cantor’s talk at QS Project page.

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QS17 Highlight: My Scars by Ellis Bartholomeus

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Ellis Bartholomeus gave a talk at QS17 that is a definite “must watch.”

We all accumulate physical scars throughout our lives. My own history consists of scrapes from trees, kitchen burns and a misadventure with liquid nitrogen. Ellis has taken a quantitative and thoughtful look at the form and meaning of her scars. At left, is a map of decades’ worth of Ellis’ scars. In her talk, she walks through that history and the way she turned it into data, which allowed novel findings, such as, if she added the lengths of her scars, the total is over a meter.

We often spend our time trying to appear and feel unworn by our years, covering them with clothing or makeup and ignoring the memories they represent. While Ellis embraces the past, she discusses the frustration associated with the limitations imposed by her injuries. Still, she uses her scars as a visual reminder to appreciate her own history and resilience.

You may watch the entire talk at her project’s page.

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QS17 Highlight: Taking on my Osteoporosis

Justin LawlerA persistent theme at the 2017 Quantified Self Conference was how self-tracking can help those with chronic conditions spot associations between symptoms and lifestyle that a clinician might not have time to uncover. These personal discoveries can help improve one’s health.

In this show&tell, Justin Lawler talks about learning that he has early onset osteoporosis and the several metrics, including diet, microbiome, exercise, sleep and bone density, he tracks to help manage and understand the disease.

I love that the talk emphasizes that many QS projects are long term – even lifelong. Most conventional research projects have a start and end date, garnering a lot of information but only addressing a limited window in time. The self awareness that comes with self tracking can be useful across months and years, elucidating subtle patterns that might otherwise be undetectable.

Watch Justin’s show&tell talk at it’s project page.

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Steven Jonas: Spaced Listening

1_Steven_SpacedListening Jan24-16.016

It’s hard for me to like an album the first time I listen to it. I can almost feel some part of my brain reject the music, even from bands I like, because it’s not familiar. However, after a few listens, the album will grow on me and I’ll find myself humming melodies that I previously couldn’t sit through. That is, unless I turned off the album the first time around and never gave it a second listen.

I suspected that this behavior was having a negative impact on my ability to appreciate new music when I noticed that almost none of the music that I listen to has come out after 2006.

In this talk, given at a recent QS Bay Area meetup, I discuss the system I set up that scheduled when I should listen to an album to help me over the hump to appreciating an album on it’s own terms instead of rejecting it because it wasn’t familiar.

Spaced_Listening_by_Steven_Jonas_on_Vimeo

Click to watch Steven’s Show&Tell talk.

Tools used:
- Anki
- Google Forms

QS17 is coming soon

Our next conference is June 17-18 in lovely Amsterdam. It’s the 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 a limited number of tickets left. We can’t wait to see you there.

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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 Wi-Fi Smart Scale

23andMe DNA Test – Health + Ancestry

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.

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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).

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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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