In this talk, Randy Sargent shows how he used a spectrogram, a tool mostly used for audio, to better understand his own biometric data. A spectrogram was preferable to a line graph for its ability to visualize a large number of data points. As Randy points out, an eeg sensor can produce 100 million data points per day. It is unusual for a person to wear an eeg sensor for that long, but Randy used the spectrogram on his heart rate variability data that was captured during a night of sleep. In the video, you’ll see an interesting pattern that he discovered that occurs during his REM sleep.
In this talk, Richard shares his attempt to improve his sleep quality by increasing the amount of bifidobacterium in his gut through eating potato starch. You’ll learn why he took the extreme step of flushing his digestive tract and rebuilding it from scratch.
I haven’t been doing these for awhile, but that does not mean that Quantified Self meetups have not been occurring. Far from it. If you are in the Washington D.C. area, there is a meetup on Friday, September 9th with presentations on using data to personalize one’s fitness regimen and how to use heart rate and EMG measurements to detect one’s sleep stage.
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 or you can search for “Quantified Self” on meetup.com. 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.
Stealth Research and Theranos: Reflections and Update 1 Year Later by John P. A. Ioannidis. This important and interesting “Viewpoint” article from JAMA: The Journal of the American Medical Association recounts the author’s first notice of Theranos and glancing involvement with the company’s publicity campaign. This leads Ioannidis, whose critical work on the validity of published research is essential reading, to offer some higher level criticism of the notion of widespread medical testing. Ioannidis’ critique draws attention to the fact that simply increasing the accessibility of diagnostic tests could be harmful, if the result is to expose people to more dangerous, costly, and unnecessary medical treatment. My take on Ioannidis critique is that changing the cultural context of testing is essential for the technological tools to be at all beneficial. For those of us who keenly desire more inexpensive and convenient blood tests, the failure of Theranos is very disappointing. However, if these tests are just treated as a kind of “look up table” linked to current knowledge and treatment protocols, they could well do more harm than good. -Gary
Smartphones won’t make your kids dumb. We think by Olivia Solon. The subject of children and screen time is hard to approach without bias. My own experience of watching my attention span get shredded to ribbons after smartphones were introduced (even though I was past the age where my brain was supposedly fully-formed) makes me feel apprehensive about the effect screen-based activities have on our brains’ reward systems. This article is particularly diligent about wading through the many aspects of this topic with the appropriate amount of trepidation and uncertainty. One thing we’ve learned from watching QS talks about distraction is that we may be more vulnerable to screen compulsion that we’re typically aware. For a poignant example, look at Robby Macdonnell’s superb QS Show&Tell talk: The Data is In, I’m a Distracted Driver. With more self-collected evidence, the worries described by Olivia Solon might be easier to evaluate. -Steven
The Challenge Of Taking Health Apps Beyond The Well-Heeled by Barbara Feder Ostrov. “There is a disconnect between the problems of those who need the most help and the tech solutions they are being offered,” so says Veenu Aulakh, the director of a nonprofit that improves healthcare for underserved patients. At the QS Public Health Symposium in May, we had an excellent session on this topic, titled “Learning About Collaboration in Community Science From from Youth Leaders in the Klamath Basin.” Driving our own research is the idea that toolmakers with positions of privilege could focus less on the design of apps to help “them” and more on listening to community leaders whose long term engagement in health issues gives them a deeper understanding of what’s useful. -Steven
How we built our Quantified Self Chatbot with Instant 4.0, by Shashwat Pradhan. For anybody thinking about building personal dashboard apps that use the native smartphone self-tracking affordances in Android and iOS, Shashwat Pradhan’s project is worth following. Pradhan is also on the QS Forum answering questions from users. -Gary
Show & Tell
40 — Mind the loops by Buster Benson. Here is an annual review, looking at his life at the age of 40, by one of the most insightful self-trackers and toolmakers in the QS community (Many of us use Buster’s 750 words for our daily journaling). -Steven
A Lifetime of Personal Data by Shannon Conners. Shannon’s workout and food journals date back to her high school years. Once digital tools were at her disposal, the diligence that she brought to her tracking has led to some amazing visualizations. -Steven
20 Years of Memories Tucked Away in Personal Finance Data by Peter Torelli. Peter tracked his finances for 20 years, and unintentionally, kept a record of the vicissitudes of his life. -Steven
Patternicity: Dreamy Diagrams and Lyrical Visualizations of the Eccentric Details of Daily Life in the City by Maria Popova. For a class, Yasemin Uyar took on the task of visualizing the minutiae of life around her for 100 days. The result is a series of dreamy and idiosyncratic takes on data visualization. The images don’t necessarily reveal the hidden patterns underlying daily life, but rather serve as a vehicle for paying attention, making the argument that merely paying attention can be a noble end, in of itself (as opposed to “hacking” to get a personal advantage). -Steven
Connected World: Untangling the Air Traffic Network by Martin Grandjean. A network visualization exercise, Martin wanted to see how to visualize all the connections between airports that makes reference to geography, but is not constrained by it (Here is an animation of the difference). For instance, a geography-constrained map would leave Europe to be an indecipherable blob of data points. The wisdom of effective visualization lies in arranging data so that otherwise hidden connections can be found. In this case, Martin discovers that “India is more connected to the Middle East than to South and East Asia. The Russian cluster is very visible, connecting airports in Russia but also in many former Soviet republics. Latin america is clearly divided between a South cluster and a Central American cluster very connected with the U.S.” -Steven
Thinking Machine 6. This is a chess game where you, as the player, can see the AI of the opponent evaluate its possible moves in real time. It’s more engaging than I expected. Especially gratifying is when you’ve put the computer into a difficult position and watch it take more time to evaluate thousands of moves to get out of the bind. I don’t think I’ve ever tried as hard to get into the head of a non-living opponent. -Steven
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Ellis Bartholomeus has many of the standard self-tracking tools like pedometers, heart rate monitors, and eeg sensors. But she explored a different type of tool when a friend gave her a logbook with a place to record her daily mood by drawing a smiley or frowny face on a colored circle.
Although it initially felt like a silly exercise, she was surprised by how she responded to these faces over time. There was a visceral pleasure to seeing these faces. Even though they were representations of her own emotional state, they seemed to take on a life of their own.
Although Ellis had the day-to-day pleasure of rendering her mood as a cartoon, she couldn’t resist the urge to structure these images to see bigger trends. You’ll see her amusing methods in the video. How do you measure a smiley face? (hint below)
Peter Torelli had $2000 saved when he entered college. He knew that it wouldn’t last long, so he had to be careful about his spending. He switched to using a credit card in order to have a record of his purchases and reconciled his accounts every month. It became a habit that he kept for a long time. A really long time.
Peter now has 20 years of financial data, and the way he’s logged his data has followed larger technological trends. Starting with manually logging transactions in Quattro Pro and storing his data on floppy disks, his data now resides on Quicken’s servers. These changes have brought better security with better backups, but also uncertainty about the ownership of his data and lack of flexibility to move his information elsewhere because of proprietary data formats.
One of the surprising findings is how many memories flooded back when he reviewed past transactions. Both memories and transactions are tied to places. A simple line item can trigger a forgotten moment with an out-of-touch friend. When Peter’s spending trends are displayed on a multi-year timeline, it’s not just a representation of his finances, but the chapters of his life as well.
There are many more great insights from Peter’s talk at the Quantified Self San Francisco meetup in April:
Taking 5: Work-Breaks, Productivity, and Opportunities for Personal Informatics for Knowledge Workers
By “approaching the question of break-taking objectives from a personal rather than an organizational angle” Daniel A. Epstein, Daniel Avrahami, and Jacob T. Biehl open a very interesting new set of questions to Quantified Self trackers and experimenters. The necessity of mental and physical renewal to work is well known and yet largely ignored. This paper, while preliminary and speculative, does us the service of challenging conventional wisdom about work breaks, showing that there is no simple definition for what activities count as breaks. -Gary
Why Talented Black and Hispanic Students Can Go Undiscovered by Susan Dynarski. Interesting article about how objective IQ testing of students for the gifted program in a Florida school district resulted in greater racial diversity. This contradicts the notion that IQ tests are biased against some groups and is a frightening indictment of teacher referral-based enrollment. -Steven
Social Network Algorithms Are Distorting Reality By Boosting Conspiracy Theories by Renee Diresta. In the battle to command our attention, media (and apps) have become like an evolving, antibiotic-resistant bacteria, finding new ways to manipulate our emotions and hijack our reward systems. The way information is presented by many online services preys on our biases, creating a new challenge for us as individuals to design our own experiences with the world to blunt the raw toxicity that is currently out there. But how do you do that in such a way that helps you become a better person, rather than creating your own, insulated bubble? -Steven
Who Will Debunk The Debunkers? by Daniel Engber. When a skeptic debunks a popular myth, it is usually accompanied by some story about how it actually happened, and how the myth spread. However, the same scrutiny is not often paid to this new story and is spread with the same lax attitude to veracity, as long as it comes from a solid-sounding source. As Daniel puts it, “It seems plausible that the tellers of these tales are getting blinkered by their own feelings of superiority — that the mere act of busting myths makes them more susceptible to spreading them.” -Steven
How maggots made it back into mainstream medicine by Carrie Arnold. According to the article, the use of maggots to clean wounds was gaining traction in the early 20th century. The practice was thrown out with the discovery of penicillin and the promise of a cleaner form of antibiotics. As bacteria have become more resistant to antibiotics, this “historical backwater” treatment is being looked at again. It’s assumed that patients would be put off by the “ick” factor, but the real barrier seems to be physcians. According to one nurse investigator: “Some care providers see it as ancient. ‘That’s old fashioned and ancient and we’re doing evidence-based practice’, which in their minds means new. But they’re not looking at the evidence behind larval debridement therapy, which there’s a lot of.” -Steven
How Information Graphics Reveal Your Brain’s Blind Spots by Lena Groeger. This is a great overview of the different tools that data visualizations can employ to help you understand a concept better and overcome some of your cognitive biases (or exploit them). -Steven
Mimicking the Fasting Mimicking Diet by Bob Troia. This is a fantastic experiment where Bob tests for himself a caloric restriction strategy where by “cutting daily calories in half for just four days every two weeks reduced biomarkers for aging, diabetes, heart disease and cancer with no adverse effects. FMD was tested on yeast, mice, and humans and the results remained consistent among all three groups.” Bob does a great job of tracking the effect the diet has on various bio-markers, showing the results visually and sharing his data. -Steven
Crying by Robin Weis is a deeply reflective self-tracking project that explores 589 days of crying data. Robin tracked every incident of crying over about a year and half, measuring and annotating 394 cries on 216 days. There is one day with 14 cries, and the longest stretch without crying is 23 days. Robin’s report from the project has many other analytic dimensions, which she uses to anchor elements of autobiography: change in in ways she handled family stress, a long stretch of travel, and an increase in awareness of injustice linked to becoming a feminist. She uses a relatively fine grained vocabulary of emotion to categories the cries. After all, as she point out: Not all cries are made equal. Some consist of a stray melancholic tear, and some consist of unstoppable laughter. Some represent the deep, achy detachment of a piece of your identity, and some can only be onset by too much hot pepper. Whatever the provocation, as soon as any emotion or sensation crosses some intensity threshold, it seems to manifest itself by physically leaking out of one’s eyes. And if that wasn’t strange enough, the thresholds appear to be drastically different across people and stimuli. What in the actual what?
Britain’s Diet in Data. Interesting interactive visualization that shows changes in British diets over the past 40 years. -Steven
Semantic Maps in the Brain. This is an incredible project where some researchers used an fMRI machine to map which parts of the brain showed increased activity in response to individual words while listening to the Moth Radio Hour. They then took that data and constructed a 3d-model and interactive visualization that allows you to select a spot in the brain and see which words are most likely to get a response from that area based on their predictive model. This page allows you to explore the semantic map of an individual. My understanding is that where we store information in our neocortex is individualistic. I wonder how much overlap you see across different people. -Steven
Ship Map. A beautiful interactive map of global shipping routes, but what sets it apart for me is the narration that introduces you to the visualization. Rather than show a video clip, it zooms around the interactive. -Steven
The Year that Music Died. This is a fun visualization that is a moving timeline of the top 5 songs on the Billboard charts from the past 60 years. As it moves through time, it will play a snippet of the song that was in the #1 spot at the time. For a bout of nostalgia, navigate to the years that you were in your early teens. -Steven
The emergence of self-tracking tools that came with the advent of the smartphone was a boon for people like Shannon Conners, who have long been recording their personal data with pen and paper. Her workout and food journals date back to her high school years.
Not content to let her data be incomplete, she has used novel sources for filling out her data sets, like going through her baby books for weight check-ins. Having a picture of her data that is comprehensive gives her a unique view. By adding annotations of major life events, she can see the vicissitudes of life reflected in her data.
Looking at her data side by side in JMP, her tool of choice, she sees how one affects the other. She determined that her cholesterol levels moved in the same direction as her weight, demonstrating to her that managing weight can be a good “surrogate variable” for keeping other biomarkers in check.
Her story may inspire you to increase your self-tracking diligence (it has for me). It has already inspired people around her. Her mother and sisters, after seeing her results with managing her weight, asked for Shannon’s coaching on how they can use self-tracking to help themselves. This is the value of sharing one’s methods: it can inspire others to change their ways of living and being.
The charts in this talk are fantastic, but they go by so quickly that I wanted to share them here so you can take them in. It should be no surprise that Shannon was featured in our QS Visualization Gallery and interviewed for the QS Radio podcast. You can keep up with Shannon on her blog, where she writes about her methods and what she’s learning.
**Update: The event is over, but you can watch the whole thing in the video below.**
Since 2014, Quantified Self Labs has put on a one day symposium in San Diego where we bring together toolmakers and public health researchers to support new discoveries about our health and the health of our communities that are grounded in accurate self-observation.
The stream starts at 9:00 AM and the schedule can be viewed here. I hope you’ll join us. Contribute to the conversation on Twitter with the hashtag #qsph16.
Abe had an issue with staying up too late. The early morning hours often found him on his couch, working on his laptop.
The problem is that he simply lost track of time. To help make his bedtime unforgettable, Abe built a reminder he could not ignore. He wrote a simple app that uses colors to gently prod him to get ready for bed and installed it on an old android phone that he mounted on the wall in his living room. When the screen first lights up in the evening, the colors are blue (“bedtime is coming.”) and increasingly become red (“bedtime is here.”). When he long-presses the screen, it means that he is ready to sleep, and the phone responds by lighting up with a celebratory array of colors.
It was a simple intervention, but did it work? Abe thought so. But the skepticism of friends spurred him to dig into the data to make sure. The problem was that his simple app didn’t record any data. He had an idea, though. For the past year, a webcam connected to a Raspberry Pi had been recording his living room. Abe used the light levels of the video stream as a proxy for his bedtime. When the light levels dropped, it meant that he had gone to bed. This proved to be a reliable indicator because, as Abe says, “I’m always the last one to sleep, and the last light I turn off is always the living room light.”
Would this work for you? Possibly not, but that’s not the point. It is an excellent example of a person building a solution that is specifically designed for his personality, and also how meaning can be found in the unlikeliest of datasets. In the video, you will find out how much sleep Abe saved and learn more about how he set up his device and ran the analysis.