Topic Archives: Videos

Christel De Maeyer: My Journey With Sleep Monitoring

Like many people, Christel de Maeyer felt that her sleep could be better. Presenting at our 2013 conference in Europe, Christel shares what she learned from collecting over three years of sleep data.


What did Christel do?
Christel tracked her sleep for 2 years with various devices. She tested the effects of different variables on her sleep quality, including consumption of alcohol, keeping a consistent wake time and changing her mattress.

How did she do it?
She used the Zeo to track sleep for two years, before switching over to a BodyMedia device. While making changes she monitored how her sleep data changed, as well as how she felt.

What did she learn?
Before self-tracking, Christel felt that she woke up frequently during the night, and the Zeo confirmed this. On average she woke up around 8 to 9 times. She suspected the mattress could be part of the problem. After considerable research, she replaced her mattress (to one that had a foam top), successfully reducing her wake-ups to 4 or 5.

Christel discovered that her sleep patterns looked significantly different after just two glasses of alcohol. Her REM diminishes to nearly 0% (though deep sleep seems unaffected).

Christel also found that total sleep time was less important for how she felt the next day than the combination of REM and deep sleep. Even if she only sleeps for six hours, as long as she gets at least 2 hours of combined REM/deep sleep, she feels good.

In addition to these findings and others she explores in the video above, Christel has taken her lessons and now helps others with sleeping issues. You can find more at her website.

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Paul LaFontaine: Upset Every Other Minute

How many times during the course of the day do you find your mental state drifting into negativity, feeling like you’re lost, or just plain stressed? How could you even keep track of this, and why would you want to?

PaulLF_upsets

What Did Paul Do?
Paul LaFontaine has been tracking what he calls “upsets” to better understand himself, the way he works, and to see if he can improve his mental and physiological response and recovery.

Upsets are something physiological that were happening beneath the surface, and they’re trackable. It didn’t have to be emotional, but there had to be a signal. This project is part of an longer ongoing study. Before this current iteration I manually logged over 3,000 upsets and what I found is that most of my upsets were self-induced. I’d be in a calm environment, but then become upset about something. I wanted to use technology because I was afraid of bias and I know I was missing some upsets.

How Did He Do It?

I used the HeartMath EMWave2 that measures heart rate variability and indicates when you’re in and out of coherence. When I was out of coherence I captured that as an upset. I would stop what I was doing and use an audio recorder to keep track of the time, how long I was upset, the reason, and what method I used to recover. I tracked 71 sessions (each session was 25-45 minutes) totaling 42 hours of tracking time. I logged 1292 upsets during this period.

What Did He Learn?
Paul analyzed his data and found some very interesting insights about his upsets, his reasons for being upset, and the effectiveness of his recovery techniques.

I found that I was triggering an upset every 2 minutes. My wife said something must be wrong with me, but this stayed relatively constant through the tracking period. I started to think of it like skiing a mogul course. The moguls didn’t move, it was about how effective I could move through them. And, dealing with upsets is like playing whack-a-mole. They come fast and furious and every second counts.

For recovery I was able to find that my most effective technique was breathing. By returning to six breaths per minute routine I was able to improve recovery time from 33 seconds to 17.8 seconds. It was the primary way I could remove myself from being upset and make myself calmer.

We want to thank Paul for presenting this great QS project at the Bay Area QS Meetup group. Make sure to watch the full talk below to learn more about Paul’s methods and findings, then hop over to his website where you can read about how he tracked his stress during this talk.

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James Norris: A Life of Firsts

Like many of us, James Norris remembers his first kiss. Unlike many of us, he also knows who it was with, where it was, and his age. How does he know this information? When he was 13, he realized that he forgot some detail about his life that he thought was important. To prevent that from happening again, he decided to carry around sticky notes to record important life events and has been doing it ever since. Fast forward 15 years and James has recorded 1,500 “firsts.” Watch this talk, presented at the Washington DC QS meetup group, to hear James talk about the data he collects, and the lessons he’s learned along the way.

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Kouris Kalligas: Analyzing My Weight and Sleep

Like anyone who has ever been bombarded with magazine headlines in a grocery store checkout line, Kouris Kalligas had a few assumptions about how to reduce his weight and improve his sleep. Instead of taking someone’s word for it, he looked to his own data to see if these assumptions were true. After building up months of data from his wireless scale, diet tracking application, activity tracking devices, and sleep app he spent time inputing that data into Excel to find out if there were any significant correlations. What he found out was surprising and eye-opening.

This video is a great example of our user-driven program at our Quantified Self Conferences. If you’re interest in tell your own self-tracking story, or want to hear real examples of how people use data in their lives we invite you to register for the QS15 Conference & Exposition.

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QS | Public Health Symposium: Jason Bobe on Participant Centered Research

As part of the Quantified Self Public Health Symposium, we invited a variety of individuals from the research and academic community. These included visionaries and new investigators in public health, human-computer interaction, and medicine. One of these was Jason Bobe, the Executive Director of the Personal Genome Project. When we think of the intersection of self-tracking and health, it’s harder to find something more definitive and personal than one’s own genetic code. The Personal Genome Project has operated since 2005 as a large scale research project that “bring together genomic, environmental and human trait data.”

We asked Jason to talk about his experience leading a remarkably different research agenda than what is commonly observed in health and medical research. From the outset, the design of the Personal Genome Project was intended to fully involve and respect the autonomy, skills, and knowledge of their participants. This is manifested most clearly one of their defining characteristics, that each participant receives a full copy of their genomic data upon participation. It may be surprising to learn that this is an anomaly in most, if not all, health research. As Jason noted at the symposium, we live in an investigator-centered research environment where participants are called on to give up their data for the greater good. In Jason’s talk below, these truths are exposed, as well as a few example and insights related to how the research community can move towards a more participant-centered design as they begin to address large amounts of personal self-tracking data being gathered around the world.

I found myself returning to this talk recently when the NIH released a new Genomic Data Sharing Policy that will be applied to all NIH-funded research proposals that generate genomic data. I spent the day attempting to read through some of the policy documents and was struck by the lack of mention of participant access to research data. After digging a bit I found the only mention was in the “NIH Points to Consider for IRBs and Institutions“:

[...] the return of individual research results to participants from secondary GWAS is expected to be a rare occurrence. Nevertheless, as in all research, the return of individual research results to participants must be carefully considered because the information can have a psychological impact (e.g., stress and anxiety) and implications for the participant’s health and well-being.

It will not be surprise to learn that the Personal Genome Project submitted public comments during the the comment period. Among these comments was a recommendation to require “researchers to give these participants access to their personal data that is shared with other researchers.” Unfortunately, this recommendation appears not to have been implemented. As Jason mentioned, we still have a long way to go.

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QS | Public Health Symposium: Doug Kanter’s Healthiest Year

We’ve featured the work of our friend and QS community member, Doug Kanter, many times here on the Quantified Self website and we were excited to have him participate in our Quantified Self Public Health Symposium. Doug is both a toolmaker and self-tracker, focusing primarily on using his experience with tracking his diabetes-related data to inform new tools and methods. In this talk, Doug explains what he learned from diving headfirst into a year-long project of tracking and visualizing all of the data he could gather about his diabetes self-management, his diet and activity, and other important factors. Beyond the wonderful visualizations he shared, Doug helped highlight something many patients and self-trackers are struggling with, the inability to access data easily and the lack of interoperability among data services and devices. We invite you to watch Doug’s wonderful talk below.

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QS | Public Health Symposium: Margaret McKenna

This week we’re taking a look back at our 2014 Quantified Self Public Health Symposium and highlighting some of the wonderful talks and presentations.  We convened this meeting in order to bring together the research and toolmaker communities. Both of these groups have questions about data, research, and how to translate the vast amount of self-tracking data into something useful and understandable for a wider audience.

As part of our pre-conference work we took some time speak with a few attendees who we thought could offer a unique perspective. One of those attendees was Margaret McKenna. Margaret leads the Data & Analytics team at RunKeeper, one of the largest health and fitness data platforms. In our conversation and in her wonderful talk below Margaret spoke about two important issues we, as a community of users, makers, and researchers, need to think about as we explore personal data for the public good.

The first of these is matching research questions with toolmaker needs and questions. We heard from Margaret and others in the toolmaker community that there is a near constant stream of requests for data from researchers exploring a variety of questions related to health and fitness. However, many of these requests do not match the questions and ideas circulating internally. For instance, she mentioned a request to examine if RunKeeper user data matched with the current physical activity guidelines. However, the breadth and depth of data available to Margaret and her team open up the possibility to re-evaulate the guidelines, perhaps making them more appropriate and personalized based on actual activity patterns.

Additionally, Margaret brought up something that we’ve heard many times in the QS community – the need to understand the context of the data and it’s true representativeness. Yes, there is a great deal of personal data being collected and it may hold some hidden truths and new understanding of the realities of human behavior, but it can only reveal what is available to it. That is, there is a risk of depending too much on data derived from QS tools for “answers” and thus leaving out those who either don’t use self-tracking or don’t have access or means to use them.

Enjoy Margaret’s talk below and keep an eye out for more posts this week from our Quantified Self Public Health Symposium.

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QS | Public Health Symposium: Susannah Fox on Secret Questions and Naked Truths

Personal data, personal meaning. That’s the guiding principle of much of the work we do here at QS Labs. From our show&tell talks and how-to’s, to our worldwide network of meetups and carefully curated unconferences, we strive to help people make sense of their personal data and inspire others to do the same. However, over the last few years we’ve started to see that there is a third actor in the Quantified Self space. Data collected in the ordinary course of life can hold clues about some of our most pressing questions related to human health and wellbeing. Personal data might be a resource for public good.

On April 3, 2014 Quantified Self Labs with support from the Robert Wood Johnson Foundation, the US Department of Health and Human Services, and Calit2 at UCSD hosted the first Quantified Self Public Health Symposium. We gathered over 100 researchers, toolmakers, science leaders, and pioneering users to open up a discussion about what it means to use personal data for the public good. Over the course of the day we hosted a variety of talks, discussions, and toolmaker demonstrations. This week we’ll be highlighting some of the outstanding talks delivered at the symposium and we’re kicking it off with one of our favorites.

Susannah Fox has been a friend and colleague for many years. Her pioneering work at the Pew Internet and Life Project has inspired us many times over and remains the standard for research pertaining to self-tracking. We asked Susannah to help us open up the meeting by discussing some of her research findings as well as her thoughts on self-tracking in the broader landscape of health and healthcare.

(A transcript of Susannah’s talk can be found on her website here.)

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Jan Szelagiewicz: Losing 40 kg with Self-Tracking

On July 4th, 2009 Jan Szelagiewicz decided to make a change in his life. After taking stock of his personal health and his family history with heart disease he began a weight-loss journey that included a variety of self-tracking tools. Over the course of a few years Jan tracked his diet, activities such as cycling, swimming, and running, and his strength. In this talk, presented at the Quantified Self Warsaw meetup group, Jan describes how he used self-tracking to mark his progress and stay on course.

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Lee Rogers: Why Annual Reporting

Lee Rogers has been collecting data about himself for over three years. The daily checkins, movements, and other activities of his life are capture by automatic and passive systems and tools. What makes Lee a bit different than most is that he’s set up a personal automation system to collect and make sense of all that data. A big part of that system is creating an annual report every year that focuses on his goals and different methods to display and visualize the vast amount of information he’s collecting. In this talk, presented at the Bay Area QS meetup group, Lee explains his data collection and why he values these annual snapshots of his life.

You can read a transcript of Lee’s excellent talk here and view his 20112012, and 2013 reports on his website.

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