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QS18 Profile: Aaron Parecki and 10 Years of Location Data

If you were to look at Aaron Parecki’s map of his hometown, there is only a slight chance you’d recognize it as Portland, Oregon. Some roads are brightly colored thick lines that stand out against a black background and others are thin, barely visible filaments that are easy to miss. There are no marked roads and no scale. It’s the last tool you’d want to use to get from point A to point B. Even so, in a different sense might be the most detailed and most personal map of Portland ever created, made from a four years of location data recorded at increments of 1-6 seconds. Aaron’s map of self-tracking data is a strong reminder that we interact with the places we live on our own terms that aren’t necessarily dictated by the roads in front of us.

portland-gps-map-aaron-parecki

Aaron’s movement in Portland from 2008 to 2012. Aaron has continued to track his location and now has ten years of data.

The image shows Aaron’s location from 2008 to 2012, but he has continued to log this information and has recently reached the ten year mark.  The tools he’s used has changed over time, but they have increasingly mirrored the deeply personal element behind the maps. Aaron’s self-designed iOS app Overland passively tracks location while the tracking server Compass stores the data, making the actual recording process unobtrusive and creating an easy platform to retroactively analyze the data. Both are open source and allow other self trackers to modify the technology to their own projects. Likewise, Aaron has developed both the app and API with the intent of individuals owning their own data. Because location tracking includes not just the physical location of a person at any point in time, but also a detailed picture of their movement habits and areas of interest, both tools include privacy controls to make sure that the user retains ownership and access to the data.

A comprehensive record of location data can easily be mapped on to mood, biological markers, or any other data recorded at the same time. With these tools, it would be possible to see how passing through a specific area of town affects mood or if a particular commute correlates with a change in weight or heart rate, giving context to metrics on how our bodies are functioning that are normally dissociated from the surrounding environment.

Aaron’s project is a good map of his own experience of Portland and the tools he uses provide a blueprint for your own location-based tracking project. He’ll be leading a workshop at the QS Conference this month, so if you want to talk about how you can apply these approaches in your own projects, you’ll have a chance to meet him there.

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We Have Posted The Conference Program for QS18!

Please join us at QS18 for over 60 first person talks, tool demos, and expert-lead workshops about self-tracking, N-of-1, and everyday science. Our focus this year is on “QS&Learning.” Along with a special plenary talk and discussion by pioneering teacher, scholar and self-experimenter Alan Neuringer, we are bringing together Quantified Self experts from all over the world to share knowledge about what we are learning about ourselves with our own data, and how we can share this knowledge with our children, students, and peers.

QS18 Conference Program

We’ll also have a special focus on open tools. One of the most powerful forces driving QS in the last two years has been the energy of DIY and open hardware makers. Many uses of data for learning don’t match well with the business models of commercial device companies, who tend to be greedy about data they collect, focused on mainstream use cases, and enthralled by the (potential) money available from traditional health care. Where does this leave individuals and communities who want to learn right now, using tools that match our needs? When you jon us at this year’s conference, you’ll meet the people creating the next generation of open tools, and using them to rapidly accelerate learning about health, sports, environment, and education – among many other topics.

All the sessions listed on our QS18 Conference Program Page have been developed in collaboration with conference registrants. We’ll keep adding and changing up until the moment the conference starts. So please be in touch and tell us what you’re working on. You can share your ideas for sessions when you register.

For a preview, here are some of the QS Show&Tell Talks we’ve announced:

Tracking Across Generations – From Journals To Life-Logging Glasses
Aaron Yih
Since the day Aaron Yih was born, his grandfather documented his life in large picture collages he hung on the walls. Now that he’s 24 and his grandfather is 84, Aaron is using digital archiving and modern lifelogging tools to make a record of his grandfather’s extensive experiences.

What I’m Learning From My Meditation App
Alec Rogers
Alec Rogers wanted to see if there was a way to measure mindfulness after meditation. He’ll talk about this and other lessons he learned using data from a simple, open source meditation tracker that he wrote himself.

Using My Training Data To Inform My Fashion
Anna Franziska Michel
Anna Franziska Michel will describe her use of her own running and cycling data as material for her startling and beautiful work in fashion design.

Blood Values Beyond Ketones – The Effect Of Exercise, Fasting, And Bathing
Benjamin Best
Benjamin Best has decades of experience with self-collected data. He’ll be talking about the analytical and graphical methods he uses to see the effects of exercise, fasting, bathing, and other common activities on his blood test values.

When Do I Do What I Say And How Does It Make Me Feel About Life
Eli Ricker
Eli Ricker tracks what he says he’s going to do and how often he does it. He’ll talk about he’s learned by connecting this data about his actions to his “life satisfaction” score.

3 Different Sleep Trackers Don’t Agree…. But What Can I Learn Anyway
Esther Dyson
Esther Dyson is obsessed with time and circadian rhythms. Wanting to understand how she slept, she started with the Zeo long ago, but now uses the Oura, Whoop, and ResMed/Sleepscore simultaneously. But what happens when this data disagrees?

Using Step And Sleep Data To Monitor Recovery
Jacqueline Wheelwright
Fitness and sleep trackers often contain built in assumptions about what’s optimal. Jacqueline Wheelwright describes how these data can be used for less common and more personal reasons.

My Headaches From Tracking Headaches
Jakob Eg Larsen
Jakob Eg Larsen predicted tracking headaches would be an easy task. But the very first question turned out to be less straightforward than it seemed: What counts as a headache? He’ll show his data and talk about his learning process over 2.5 years.

Exercising Without Glucose Which Is Supposedly Impossible
Jessica Ching
Bay Area QS Show&Tell participants may remember Jessica Ching’s wonderful talk about training dogs to detect low blood sugars. This year she’ll show data about a different project: learning how exercise without glucose.

I Made Polyphasic Sleep Work For Me
Jonathan Berent
You’d have to be a crazy to think you could get by on 2.5 hours of sleep. Jonathan Berent is that kind of crazy. He’ll show data from his polyphasic sleeping, the effects this had on his life, and what he still hopes to discover.

Can Tracking Devices Detect And Help Me With Having Low Energy For An Extended Period?
Justin Lawler
Justin Lawler has been dealing with low energy for the past 6 months. An avid self-tracker, he wanted to see how well the currently available tools capture this feeling and help him along a path of improvement.

An N-of-2 Study with My Best Friend About How to Lower Blood Pressure
Karl Heilbron, Fah Sathirapongsasuti
With a family history of stroke and early warning signs of hypertension, Fah Sathirapongsasuti recruited friend and fellow scientist, Karl Heilbron, for a two person self-study of how lifestyle influences their blood pressure.

What InsideTracker Taught Me About My Five-Day Fast
Kyrill Potapov
Kyrill Potapov tested theory that a fast can clear out the digestive tract and repopulate it differently. He shares his results from a 5 day fast, using InsideTracker panels to test his before and after states.

A Self-Study Of My Child’s Risk Of Intellectual Disability From A Rare Genetic Variant Carried By My Family
Mad Ball
Mad Ball is a carrier for a rare genetic disease which entailed risk of having a child with a serious intellectual disability. But how much risk? Through careful self-investigation based on consumer genomics, a reasonable estimate turned out to be possible.

The Cost of Interruption
Madison Lukaczyk
Madison Lukaczyk tracked her time to see the impact that interruptions had on her productivity; the data and analysis changed how she uses her communication tools.

Learning From 5000 Pomodoros
Maggie Delano
Maggie Delano used the Pomodoro method – 25 minutes of work followed by 5 minutes of anything else – to complete her Ph.D. Her 5 years of Pomodoro data challenges the assumption that working all the time is the key to accomplishing things.

5 Years Of Tracking And Visualizing Posture Data
Esther Gokhale, Mark Leavitt
How can a sensor accurately detect whether your back is aligned? Mark Leavitt and Esther Gokhale have been working on this problem for years and they share how they used their data to improve their posture.

Running Three Marathons On Zero Calories
Mikey Sklar
Mikey Sklar ran three marathons in one day. He consumed liquids for hydration and metabolites but no calories. He’ll show how he used personal data to understand how this seemingly impossible feat could be accomplished.

Which Grasses Aggravate My Allergies
Thomas Blomseth Christiansen
Thomas Christiansen’s allergies are aggravated when running during grass pollen season. For this extremely clever project he used a GoPro to document passing vegetation and a device to record his sneezes in order to pinpoint what plants activated his nose.

Learning From My Whinges
Valerie Lanard
Valerie Lanard keeps a detailed workout spreadsheet. In her “notes” section, she wrote out whatever excuse she had for not working out. Over time, she realized that this was a rich dataset on it’s own, detailing what’s happening when she’s not exercising.

Cholesterol Levels While Nursing
Whitney Erin Boesel
After giving birth, Whitney Erin Boesel learned that her cholesterol was very high. Given her family history, it seemed that an intervention was in order. But what if she did nothing and simply made observations?

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Erica Forzani: Understanding My Pregnancy

Following closely behind Whitney’s pregnancy project, it is fitting to share Erica Forzani’s pregnancy tracking project that can inspire any human who has carried a human in her belly. In addition to just being pregnant and dealing with the work involved with growing a human, Erica tracked her blood glucose levels, physical dimensions, weight, resting metabolic rate, activity, blood pressure and diet throughout her pregnancy to argue many pregnancy and breastfeeding myths. There are a lot of them and her diligent work proves many false.

I’m not quite sure what it is, but for some reason, people love to give pregnant women and women with babies/kids feedback about whatever they are doing. Be it positive or negative, some people just can’t help offering some bit of information they are observing. Perhaps it is because, procreating is somehow instinctively shared among humankind, so people somehow feel they have a piece-in-the-game with the raising of any little being…whatever it is, Erica’s project politely and factually stomps out many of the myths people often hear while carrying a human.

We hope you can join us to share your learnings from a project, or simply be inspired at this year’s 2018 Quantified Self Conference in Portland on September 22-23. Register here.

 

 

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Tracking Mood: Jon Cousins

When talking about tracking mood and happiness at Quantified Self, we have to mention Jon Cousins, an active QS member and long-time mood tracker. In 2010, Jon created Moodscope to track is own mood, and left in 2013 to begin Moodnudges, where he writes short messages to help nudge one’s mood in a positive direction. He released a book on the topic called Nudge Your Way to Happiness.

Jon presented his more recent self-tracking project, Words for Mood Measurement, at the Bay Area Quantified Self meetup on April 19, 2016.  Jon shares his experiments with Word Stem Completion tasks to better understand his mood.

The tests work like this: You are given the first part of a word and asked to complete it. For instance, if the stem is “ang__”, you might complete the word as “angle”. But if you are feeling frustrated, “anger” is probably more likely to come to mind.

Watch the video at Jon’s project page to learn from his insightful project and perhaps grab some take-aways for trying this on your own.

Jon Cousins presents his project at the Bay Area QS meetup

Jon Cousins presents “Words for Mood Measurement” at the Bay Area QS meetup. Follow Jon Cousins on Twitter.

Jon holding his book "Nudge Your Way To Happiness"

Jon holding his book Nudge Your Way To Happiness

Join us to share your learnings from a project, or simply be inspired at this year’s 2018 Quantified Self Conference in Portland, OR on September 22-23. Register here.

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Tracking Happiness: Ashish Mukharji

Another conceptually simple idea, but still just as profound, comes from a project by Ashish Mukharji called Tracking Happiness, presented at a Bay Area Meetup in 2013. It’s another great example of the timelessness of QS projects. QS’ers are constantly asking ageless questions where the answers are often in flux as our bodies and minds grow. It’s fascinating to reflect back on both what we are learning individually and collectively at Quantified Self; for, the confirmation from similar answers, makes the projects all the more profound.

Ashish is the author of Run Barefoot and Run Healthy. In 2010, Ashish bought a book called How of Happiness for an extra boost in happiness. He wasn’t unhappy, but he enjoyed the instructions the book provided and began tracking his happiness for three years, rating each day with one number between 1-10.  He learned that he is on average a 7 out of 10. But, more importantly, through tracking his happiness, he learned that it was most greatly affected by sleep and other variables such as mean people and solitude.  After tracking his happiness for three years, he essentially learns some important tools to help keep his life as happy as possible. (Certainly a worthwhile project for all of us to learn from!)

We hope you can join us to share your learnings from a project, or simply be inspired at this year’s Quantified Self 2018 Conference in Portland on September 22-23. Register here.

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Music Habits Analyzed Through Tracking: Steven Jonas

Steven Jonas presented his interesting project, Spaced Listening to the Bay Area Meetup Group at the Haas School of Business, UC Berkeley in 2017. In this project, Steven takes a very active role in his music engagement to increase his listening palate.

Steven knows that he needs to listen to an album a few times before he begins to like it. Despite knowing this, he found that he often chose not to listen to a new album because he knew it would be somewhat unpleasant. In this talk, he shows a system he created that schedules when he should listen to a particular album in the hopes that it would lead him to liking new music.

Steven's timing schedule of when to introduce new songs

Steven’s timing schedule of when to repeat new songs

We hope you can join us to share your learnings from a project, or simply be inspired at this year’s Quantified Self 2018 Conference in Portland on September 22-23. Register here.

 

 

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The Ethics of Citizen Science, A Call for Papers

Here’s an interesting call for papers for citizen scientists by the journal Narrative Inquiry in Bioethics published by Johns Hopkins University Press.

The editors want first person accounts of ethical issues in citizen science. I’ve been part of many discussions of whether QS is part of citizen science. There are some key differences. The most important reason not to think of QS as citizen science is that most QS projects are not designed to contribute to research problems in a scientific discipline. Instead, they are meant to answer one person’s question. The answer may be interesting to science, it may even make a novel contribution, but the disciplinary nature of science, and the non-disciplinary nature of QS, is a distinction too important to ignore. And yet, with all that said, I still think this call for papers is interesting to disseminate.

First: I know that many people who do QS projects face interesting ethical questions, and some of the thinking associated with this work might be interesting in the more institutional context of citizen science. And second: there are an increasing number of QS projects that take place among small groups; while each person has their own reason to participate, the social nature of the projects brings them closer to the kind of group research typically done by citizen scientists. I’m curious about the ethical issues of doing group projects, and I’d like to know how others are handing them. For the Bloodtesters group that I helped organize, we ended up using a process of ethical reflection we called – only somewhat tongue-in-cheek – “self-consent.” What have you done?

The full call for papers is here: Narrative Inquiry in Bioscience

Excerpt:

Narrative Inquiry in Bioethics will publish a collection of personal stories from individuals involved in citizen science research. Citizen science is a growing area in which the lay public is involved in research in dynamic and important new ways. This enables new questions to be asked, new methods to be pursued, and new people to contribute, often without the usual oversight provided by institutions and funding agencies. Citizen scientists do environmental research, animal research, human research including clinical trials, identification of photographs, or collect other data.

This movement has implications for traditional science and for human participants in trials run by citizen scientists. Among some of the most challenging and interesting are the ethical implications of this new scientific research.

We want to collect true, personal stories from citizen scientists and those who contribute to citizen science. Please share this invitation and guide sheet with appropriate individuals. In writing your story, please consider one or more of these questions:

  • What does citizen science enable that conventional research approaches do not?
  • What unique challenges have you faced doing citizen science?
  • What ethical issues have you confronted in the conduct of the research?
  • Were you able to use existing frameworks (such as Institutional Review Boards) to resolve them, or did you approach resolving the ethical issues in a new way?
  • What advice would you have for individuals who are considering conducting their first citizen science project?
  • What advice would you have for those who seek to regulate citizen science?
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Meetups This Week

QSMontrealJuly

 

This week there are two QS meetups happening. On Thursday, Gary Wolf will be hosting a somewhat unusual meetup at the National Archive in The Hague. Self trackers and archivists will get together to discuss current trends and issues around personal data and quantified self, including archiving methods and data privacy.  The Hong Kong meetup will also get together on Thursday to share what they’ve learned from their own genomic data.

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, November 16th

Amsterdam, Netherlands

Hong Kong, China

 

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Quantified Self Guide to Tracking Cholesterol and Triglycerides

What is a QS guide?

The purpose of a QS guide is to make it easy for you to start tracking a new metric. Searching for the right device, head-scratching over how to use the thing, and figuring out what experiment to try first can be a huge time sink. Our goal is to offer a worked example of all of these steps with the device(s) we found to be the best on the consumer market. While the most sophisticated tools for physiological measurements are offered through professional laboratories, our guide is – of course – meant to help you with your own, DIY self-tracking projects. It’s not an extensive review of every option, but it will lead you from purchasing, to validating, to syncing the data, to doing a first experiment. As you go through the process yourself, much of your learning will come from building a mental model of how your own physiology works through additional reading and experimentation. Don’t shy away from that work – a QS project may not answer your question expediently, but it has the potential to teach you a lot.

The Guide to Tracking Cholesterol and Triglycerides will discuss two home lipid trackers: the CardioChek Plus and the Cholestech LDX. I will give an in-depth review of my experience with the former. The guide will touch on the science of the tests and devices, their accuracy and precision, and suggest a first experiment to try.

A little about blood lipids

While we normally think of cholesterol and triglycerides as risk factors for heart disease, there’s actually much more to them. In fact, it turns out that the basic functions of lipid components — including total cholesterol, triglycerides, HDL-c and LDL-c, not to mention their roles in heart health — are an active area of research and the center of an ongoing controversy. What lipid measurements can certainly do is reflect how your body is handling ingested animal products and fats. If you’d like to learn more, we put together an animation that goes a little deeper into the physiology.

40450Option 1: CardioChek Plus

What It Does:  The CardioChek Plus measures blood lipids including total cholesterol, HDL-c and triglycerides using test strips. The device itself is battery powered and about the size of a Game Boy Color (and it makes similar sounds!). Each sample requires 40ul of blood and takes a few minutes. The major limitation of the device is its range of operation (it won’t report results if your lipids are very high or very low -and different lots of test strips have different operating ranges. Be sure to read the documentation before you purchase). It is an FDA approved, CLIA waved, testing system for clinical and paraclinical use.

Cost: New units retail for ~$800-$1000, but units appear on eBay for around $400. The tests cost ~$15 each and come in bundles of 15. Additionally, you will need rubbing alcohol, 2.8 mm lancets40 ul capillary tubes for blood collection and gauze wipes. Cost of extra supplies comes to about $200 for 15 tests.

Getting Your Data: The CardioChek stores data locally and has a limited memory. We recommend transferring the raw data by hand (3 numbers per test) to a personal spreadsheet.

Accuracy, Precision and Supporting Research: Finding information about the accuracy and precision of a new device can be non-trivial. Confirming what you learn can be even harder. We’ve had several months to figure out measurement validity for home lipid testing, and it’s a little complicated. At present, there is measurable variability (~13% is acceptable) in results obtained from clinical laboratory tests (Quest, LabCorp) as well as those from para-clinical tests like the CardioChek Plus. Chris Hanneman has written a great report that comments on the not-very-useful way validations are reported by glucose meter companies – and we acknowledge that the same is true here. The company that produces the device, PTS Diagnostics, reports numerous validations at the bottom of this page under resources, but we’ve averaged the basics across these many reports to produce a summary table. 

Accuracy is a measure of how close a measured value is to the true value of the measurement (obtained via some gold-standard device). For accuracy, PTS diagnostics reports 18% error for total cholesterol (averaged across reported tests on the website in this document), 8% for HDL-c, and 13% for triglycerides.

At least one academic group has published a validation of this device: Gao et al., 2016 . They reported 3% error for total cholesterol, 7.1% error for HDL-c,  and 7.6% error for triglycerides.

Precision is a measure of agreement between two measures which should be identical. In other words, it’s a measure of how much noise the device adds to the signal. During our own testing we measured the precision of the CardioChek Plus; you can view our results here. We actually found the CardioChek to be more precise than the company reports (so far).

 

Cholestech LDX Analyzer OnlyOption 2: Cholestech

What it Does: The Cholestech LDX also measures total cholesterol, HDL-c and triglycerides. However, the device is larger (shoebox sized) and less mobile than the CardioChek Plus — it must be plugged into an outlet and calibrated in each new location.

Cost: New units retail for ~$2000, but used units can be easily found on eBay for around $50-$100 each.Note: make sure units have ROM pack version 3.40 or higher, and calibrate the used device.

Getting Your Data: Similarly, we recommend transferring the raw data by hand (3 numbers per test) to a personal spreadsheet.

Supporting Research: Whitehead, 2014 offers accuracy and precision measurements. Bias was 11.6% for total cholesterol, and 12.9% for HDL-c.  The authors reported %CV of 2-3.5% for HDL-c and total cholesterol (pretty good!) – with the caveat that the venous blood samples they compared are less likely to introduce measurement error in comparison to the finger prick samples used at home.

My Experience, and What I Tried First

I only had the opportunity to use the CardioChek Plus, but my comments should apply to both devices. Setting up the device is trivial, but testing requires a few practice trials.  The main challenge is the amount of blood required; it’s forty microliters (µl) which is equivalent to 2 large drops of blood. For some people I worked with, this was easy. But for others like myself, running the sampling hand under a hot tap is necessary to get the blood flowing. On top of this, the blood needs to be collected and deposited on the test strip within a couple of minutes to get an accurate reading. If this sounds a little off-putting, don’t worry too much- one becomes a blood collecting ninja fairly quickly. The pay of is in the ability to learn what my lipids are doing in near-real-time.

A First Experiment

While preparing for the project I wondered how fast my lipids really changed. I knew that seasonal, ovulatory cycle, and daily changes in lipids had been reported in the literature, but I wasn’t able to find any examples of how individual ambulatory humans varied hour by hour. The dynamic actions of these compounds on short timescales are less well characterized than changes on the timescale of years, but they are likely to contain useful health information. Because of all of this, I decided to measure my lipids every hour from the time I woke up, to the time I went to sleep. I won’t go into everything I saw here, but I will share one picture.

Azure cholesterol fig

I’m 22 and in good health, yet across a single day I saw my total cholesterol nearly 50 mg/dL (almost plunking me into the at-risk for CVD category). Even more interesting, these changes seemed to occur at regular 3 h intervals, gradually climbing higher until they peaked around 8 pm. I learned that these changes might actually tell me more about my health than any one of those measurements alone could have.  If you’re interested in getting a general sense of what your lipids are doing before you dive into more complex tests, I highly recommend setting a date with your CardioChek Plus or Cholestech LDX for some hourly measurements. Want a more in-depth argument for why you should try this first? Check out this animation.

This guide may have revealed that blood lipids are more complicated than you thought. But there’s no need to be overwhelmed — explore the metric, and you’ll build a deep understanding of your lipids in the process.      

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Meetups This Week

Screen Shot 2016-11-30 at 11.10.36 AM

Two meetups this week are happening on opposite sides of the U.S. If you’re interested in what happened at our conference in Amsterdam – or alternately what one man’s physiological response to seeing a bear was – then the Portland meetup is the place to be.

If you are on the East Coast, the D.C. meetup group has a great lineup of talks from students and faculty of John’s Hopkins University this Saturday. The meetup will host an introduction to tracking your metabolism and circadian rhythms by Tom Woolf, tracking your productivity with the OmniTrack platform by Eun Kyoung Choe, and insights from running and HR data.

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, October 17

Portland

Saturday, October 21

Washington D.C.

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