Topic Archives: Videos
Mark Drangsholt has been dealing with an issue with his heart since he was a young man. Since his early twenties, when he as diagnosed with paroxysmal atrial tachycardia he’s had to deal with irregular heart rhythms. In this talk Mark explains how the transition into adulthood negatively impacted his health and then how he used self-tracking and a focused athletic program to help him reduce his weight and improve his health. Most show&tell talks would end there, but Mark still had the irregular rhythm issue to deal with. After what he describes as an episode that made him think, “This is it. I’m going to die.” he decided it was time to apply his self-tracking process in order to understand his heart rhythm disorder and possible triggers. Mark also decided to go one step further and apply the principles of case-crossover design to his tracking methodology. Watch his talk below and keep reading to learn a bit more about why you might want to consider using case-crossover design in your self-tracking projects and experiments.
The following excerpt from the QS Primer: Case-Crossover Design by Gary Wolf provides a great background for his method:
Mark’s self-tracking data didn’t naturally fit with any of these approaches. To understand whether these triggers actually had an effect on his arrhythmias, he used a special technique originally proposed by the epidemiologists Murray Mittleman and K. Malcolm Maclure. A case-crossover design is a scientific way to answer the question: “Was the patient doing anything unusual just before the onset of the disease?” It is a design that compares the exposure to a certain agent during the interval when the event does not occur to the exposure during the interval when the event occurs.
Using this method, Mark discovered that events linked to his attacks included high intensity exercise, afternoon caffeine, public speaking to large groups, and inadequate sleep on the previous night. While these were not surprising discoveries, it was interesting to him to be able to rigorously analyze them, and see his intuition supported by evidence. “A citizen scientist isn’t even on the conventional evidence pyramid,” Mark notes. “But you can structure a single subject design to raise the level of evidence and it will be more convincing.”
“Personal experimentation is simply tracking, on a schedule.”
Ian Eslick is a scientist, researcher, and self-tracker. His unique history has led him down a path towards understanding what it means to understand yourself and your health in and outside the world of healthcare. Ian’s health history helped push him down this path. Since being diagnosed with psoriasis he’s been confronted with the difficult task of figuring out triggers, effects, and treatments as his symptoms changed over time. Ian, began to explore self-tracking by mentally noting what was going on in his life and his symptom severity. You would think that this “in my own head” tracking methodology would limit analytical capabilities, but it helped Ian create mental models that informed more consistent and rigorous tracking methods, as well as influenced his future research.
In this talk below Ian describes that research, both personal and community-based, that explored the concept of helping people learn how to create and engage with personal experimentation.
“What I came to in conclusion after all of this is that N of 1 is overkill for QS. It’s unnecessary level of rigor. Ninety-five percent confidence intervals are about scientific causal proof, but what I want to know is am I making a better decision. Is data improving my decision in some measurable way? Not is it a perfect decision or do I have proof. So we want to value personal significance over statistical significance. Statistical significance says that if I run this trial twenty more times I’m likely to get the same result, but what I want to know is should I keep doing this and in QS we’re never going to stop keep experimenting, in a way, because our life keeps going.”
We’ve all come face to face with tracking some aspect of our life only to realize that we’re not quite sure how to get started. Enrico Bertini encountered this roadblock when he began thinking about tracking the amount of time he spends engaging in “focused work.” As an information visualization researcher at NYU he decided on a simple rule that would give him the most accurate data that represented his interests: if it wasn’t tracked then it wasn’t focused work. In this talk, given at the New York QS meetup group, Enrico explains his process and shares his findings (including some great visualizations).
Slides available here.
(Editor’s Note: Enrico also co-hosts a great podcast on data visualization and information design called Data Stories. I highly recommend listening. If you’re looking for a place to start try Episode 17: Data Sculptures.)
A big piece of our work at QS Labs is supporting our worldwide community through the over 100 Quantified Self Meetups (see our sidebar at right). At our local meetup in the Bay Area, and others we’ve had the pleasure of visiting, we are consistently observing that nearly half of the attendees are new to the Quantified Self. Considering this, Gary Wolf, our director and co-founder, gave a short presentation to introduce our work and how we see the Quantified Self as a cultural and technological movement. If you’re new here, or just want to reorient yourself, watch Gary’s excellent talk below.
“If I look at this, I have these memories, and I remember this was a good year.”
Collect it and forget it. This could be be hidden mantra of many people engaged with self-tracking, myself included. I will readily admit to buying a device or application with the hope that I can collect enough information to generate a grand insight at some mythical point in the future where the intersection of free time, analytical knowledge, and sample size magically coalesce. Ulrich Atz encountered the same problem. He was tracking, but soon lost sight of the purpose. Rather than giving up he started a new tracking project.
Ulrich started by building on the popular habit and tracking theory, Don’t Break the Chain, based on consistency in behaviors you care about. He identified six major categories he wanted to understand and pay attention to: his evening ritual, fitness, nutrition, learning, sleep, and travel. Rather than using an passive tracking system like Foursquare of Sleep Cycle, he decided to keep track of it by writing on a large wall calendar. In this presentation, given at the London QS meetup group, Ulrich describes his methods and what he learned from this year-long process.
Science. Someone makes an observation, creates a hypothesis, tests it, then analyzes the results against the hypothesis. Hopefully once a conclusion is reached it is tested again and again for validity and reproducibility. With self-tracking, the world of personal science and experimentation is opening up real-world personal laboratories to test the findings, claims, and promises available through the popular and scientific literature.
Nick Alexander is one of these self-experimenters. When he started to hear about thermodynamics and the effect of temperature on exercise and energy expenditure he decided to set up his own experiment:
I had been introduced to thermodynamics exercise research by former NASA scientistRay Cronise via Wired and the Four Hour Body. Ray makes an extraordinary claim (i.e. that exercising in a cold environment, especially in cold water, causes a large increase in calorie burn), and I was curious to see if it would work for me.
In this talk, given at the 2013 Quantified Self Global Conference, Nick explains his experimental setup and what he found after tracking over 30 runs and crunching the numbers. For a more in-depth discussion about his methodology and his findings I recommend reading his recaps.
This video is from our 2013 Global Conference, a unique gathering of toolmakers, users, inventors, and entrepreneurs. If you’d like see talks like this in person we invite you to join us in Amsterdam for our 2014 Quantified Self Europe Conference on May 10 and 11th.
There are no shortage of apps and devices to track our various physical activities. Going for run? A few laps at the pool? An early morning hike? All of these are trackable with data delivered and archived in a variety of different ways. Mike McDearmon loves to get outdoors, and he also loves tracking his activities. What started as a project to document his runs by taking a picture every time he went running has evolved into a fascinating mixed-media project. Since 2011 Mike has been taking a picture every time he exercises outdoors. In this talk, presented at the New York QS meetup group, Mike explains his methods, and digs a bit deeper into what this means to him.
For me, the real value in this whole project hasn’t necessarily come from the data at all, but from the process of getting outdoors, exploring my surroundings, taking photographs, and then reflecting on my experiences through documentation. This is what I feel is at the heart of the Quantified Self movement – it’s the passion and enjoyment in certain aspects of our lives that makes us want to document them in the first place. – from 300 Outings.
Download slides here.
I highly suggest taking the time to peruse Mike’s wonderful website where he documents his running, cycling, hiking, walking, and the pictures he’s talking along the way. He’s also built a really neat data dashboard that is worth perusing.
Kevin Krejci was diagnosed with Parkinson’s Disease last year. At a recent Bay Area QS Meetup, Kevin shared his story of how he’s using self-tracking applications and devices to help him monitor different symptoms and outcomes related to his diagnosis. Watch his talk below to hear about his triumphs and challenges.
Rob Rothfarb has an artificial aortic heart valve. It requires him to take anticoagulation therapy so that he reduces his risk of blood clots. It also requires constant monitoring to ensure that he is within target ranges. Rob learned that different lifestyle factors and genetic susceptibility was related to how effective his therapy was so he decided to start doing weekly self-testing and experimenting with one factor, his diet. Watch his talk from our 2013 Global Conference to find out what he learned.