Tag Archives: withings

What We Are Reading

Enjoy this week’s list!

News

You’re invited to join us on June 20th for an amazing day of demos, talks, and sessions highlighting the very best of the Quantified Self at our QS15 Expo. Readers of What We’re Reading get a special discount. Just click here to get $10 off your ticket price.

We’ve received some amazing entries in our Future Normal QS15 Challenge, so amazing that we’ve extended the challenge a few days. If you’re reading this before Monday, June 1st make sure to enter nowfor your chance to win two free Ultimate Panels!

Articles

I’m the New CTO of HHS by Susannah Fox. So great to see this announcement. All of us at QS Labs have the utmost respect and admiration for Susannah and her dedication to positively impacting human health. Additional posts and articles about Susannah’s appointment can be found here and here.

As technology savvy as Susannah is, it is her capacity to hold a huge vision, and keeping patients at the center of that vision, that make her so deeply qualified for this job. No body asked me who the next CTO of the government was going to be, and frankly I was a little worried about who would be next. Bryan Sivak and Todd Park (her predecessors in this role) leave pretty damn big shoes to fill. Someone in the Whitehouse/HHS is casting a net wide enough to know who the really transformational thinkers in our industry are. – Fred Trotter

Special Report: Hacking the Human OS by IEEE Spectrum. A fantastic three-part report here by folks over at IEEE. This collection of articles, infographics, and op-eds is a must read.

Public Health and Tech: Long Lost Lovers? by Vanessa Mason. A short but nice article outlining how technology may interface with Public Health practices and program implementation. Great to see a mention our RWFJ supported Quantified Self Public Health Symposium.

The quantified self in a complex system: A systems perspective on mental workload by Steven Shorrock. A great post here by Steven concerning the role of quantitative information in dynamic and often complex human systems (like your workplace).

For these reasons, most numerical measures concerning human experience and system parameters should be treated as social objects. Any data on mental workload, sector capacity values, traffic numbers, or whatever, are a reason for a conversation, the start of a conversation – not an end point.

Show&Tell
milesCompBar
Apple Health App and My Quantified Self by Nadine Fischoff. One day Nadine realized her iPhone was keep track of her daily activity (steps and distance walked) so she decided to dive into the data to see what she could learn. With the help out our QS Access app (download it today – it’s free!) she was able to access, download, and analyze her data. What did she learn? Moving to New York City from Mountain View increased her daily walking 48%!

2014 Writing Progress by Ben Wilson. A great post here by Ben describing his writing progress over 2014. Ben tracked his goal of writing two novels in 2014, and ended up tracking over 90,000 words written.(Found via the always excellent Exist.io Blog.)

Visualizations
Screen Shot 2015-05-30 at 11.43.17 AM
Withings Health Observatory: Blood Pressure by Withings. Great to see Withings has added blood pressure to their real-time data dashboards.

Visualizing the Quantified Self: Giving Form to Lifelogging by Fil Greenwich. A nice overview post of different data visualizations.

From the Forum

GPX Import to Google Fit
Measuring Anxiety Using Smartphone Sensors
Is there a smartwatch app akin to Reporter or KeepTrack?

This Week on QuantifiedSelf.com

Welcome to Our QS15 Friends of QS

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What We Are Reading

Below you’ll find this week’s selection of interesting bits and pieces from around the web. Enjoy!

Articles
Open Books: The E-Reader Reads You by Rob Horning. A fantastic essay about the nature of delight and discovery, and how that may (is) changing due to data collected from e-readers. For those interested in books and data this article By Buzzfeed’s Joseph Bernstein is also an interesting read.

Flashing lights in the quantified self-city-nation by Matthew W. Wilson. Quantified Self, smart cities, and Kanye West quotes – this commentary in the Regional Studies, Regional Science journal has it all. Read closely, especially the final paragraph, which gives space to think about the role the institutions and companies that provide cities with the means to “be smart” have in our in social and urban spaces.

Most Wearable Technology Has Been a Commercial Failure, Says Historian by Madeleine Monson-Rosen. This is a interesting book review for Susan Elizabeth Ryan’s Garments of Paradise which had me thinking about the nature of wearables, customization, and expression.

‘The Cloud’ and Other Dangerous Metaphors by Tim Hwang and Karen Levy. This was mentioned so many times over the last few days by so many smart friends and colleagues that I had to set aside time to read it. It was time well spent. The authors make the case that how we talk about data (personal, public, mechanical, and bioligical) is tied to the metaphors we use, and how those metaphors can either help or hinder the broader ethical and cultural questions we find ourselves grappling with.

Why the Internet Should Be a Public Resource by Philip N. Howard. This isn’t the first, nor will it be the last, argument for changing the way we think about and regulate the Internet. Worth reading the whole things, but in case you don’t consider this point:

And then we might even imagine an internet of things as a public resource that donates data flows, processing time, and bandwidth to non-profits, churches, civic groups, public health experts, academics, and communities in need.

Computers Are Learning How To Treat Illnesses By Playing Poker And Atari by Oliver Roeder. How does research into algorithms and AI intended for winning poker games morph into something that can optimize insulin treatment? An interesting exploration on the background and future implications of computers that can learn how to play games.

Data Stories #45 With Nicholas Felton. by Enrico Bertini and Moritz Stefaner. In this episode of the great Data Stories podcast Nicholas Felton talks about his background, his interest in typography, and what led him to start producing personal annual reports. Super fun to listen to them geek out about the tools Nicholas uses to track himself.

Increasingly, people are tracking their every move by Mark Mann. A great peak into some of our QS Toronto community members and how they use self-tracking.

Quantified Existentialism by Ernesto Ramirez. I’m putting this last here because it feels a bit self-congratulatory. Earlier this week I took some time to examine how common it is for people to express their relationship with what counts when they use self-tracking tools. It was a fun exercise.

Show&Tell
Insights From User Generated Heart Rate Variability Data by Marco Altini. While not a personal show&tell (however, I’m sure his data is in there somewhere), this great post details what Marco was able to learn about HRV based on 230 users and 13,758 recordings of HRV.

Quantify This Thursday: No Coding Required by Kerri MacKay. A bit different post here, more of a how-to, but I found it really compelling the lengths Kerri went to get get her Fitbit data to show up on he Pebble watch. I was especially drawn to her explanation of why this method is important to her:

The reality is, getting nudges every time I look at the clock or dismiss a text notification on my Pebble (via my step count) is yet another way to make the wearing-a-wearable less passive and the data meaningful.

Correlating Weight with Blood Pressure by Sam. A short and simple post detailing how Sam used Zenobase and his iHealth devices to see how weight loss was associated with his blood pressure.

Visualizations
WithingHolidays
The Effect of End of Year Festivities on Health Habits by Withings. The above is just one of four great visualizations from Withings exploring how the holidays affect how users sleep, move, and weight themselves. Unsurprisingly people are less likely to weight themselves on Christmas day (I looked at my data, I am among those non-weighers).

SimonData
Simon Buechi: In Pure Data by Simon Buechi. A simple, elegant dashboard intended to represent himself to the world.

MatYancy_Coding
Grad School Coding Analysis by Matt Yancey. The above is just a preview of two fantastic visualizations that summarize the coding Matt did while enrolled in the Northewestern Masters of Analytics program.

Fitbit_NewYears_Steps
News Year’s Eve Celebration in Steps by Lenna K./Fitbit. A fun visualization describing differences in how people in different age groups moved while celebrating the new year.

From The Forum
How do I visualize information quickly? (mobile app)
Monitoring Daily Emotions
Best Heartrate Monitor that syncs with Withings Ecosystem
Is the BodyMedia Fit still alive?
Capture Online Activities (and More) into Day One Journal Software (Mac/iOS)

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Jamie Williams: Exploring my Data

JaimeWilliams_FullFitbitData

Jamie Williams found himself with almost two years of self-tracking data including physical activity, blood pressure, and weight. Because of his interest in data visualization and coding he decided to learn how to access it the data and work on visualizing and understanding some of the trends and patterns. In this talk, presented at the QS St. Louis meetup group, he takes a deep dive into his activity and step data as well as his blood pressure data to learn about himself and what affects his behavior and associated data.

What Did Jamie Do?
Out of pure interest in seeing what the data would reveal, Jamie utilized a combination of devices to track his physical activity, blood pressure, heart rate, weight, numbers of drinks, and automobile travel. He then went on to explore ways in which he could pull down, integrate, visualize, and ultimately make sense of what he collected.

How Did He Do It?
In order to obtain his data on a minute-level resolution, Jamie had to email FitBit for a specialized use of their API. He then employed Mathematica to develop a number of (beautiful) visualizations of his activity – along with other key moments in his life (moving to St. Louis, changing job location, preparing for a Half Marathon, etc.). Jamie was able to compare his data not only to his peers through FitBit, but also to others of his demographic in the U.S. using the publicily available NHANES data set.

What Did He Learn?
Through Jamie’s Quantified Self collection and analysis efforts, he learned a lot not only about the patterns and changes in his activity, but why they were the case. He also presented great feedback about one’s mindset when comparing to peers vs. the general population.

Tools
Fitbit
Withing Blood Pressure Cuff
AskMeEvery.com
Automatic
Mathematica
D3.js
Python

Thank you to QS St. Louis organizer, William Dahl, and Jamie for the original posting of this talk!

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Ralph Pethica: Improving My Fitness With Genetics

1_RalphPethica_QS Talk 2014 Powerpoint

One interesting aspect of personal data is how it can reveal what is unique about you. Nowhere is this more true than with genetic information coming from DNA testing kits. However, people are still at an early stage on how they apply that information to their lives. Ralph Pethica, who has a PhD in genetics, was interested in what his DNA could tell him about how to train more effectively. His findings were presented as an ignite talk at the 2014 QS Europe Conference.

What did Ralph do?
Ralph loves to surf. When it is the off-season, he trains so that his body will be in good condition for when the warm weather rolls back around. He used genetic research to inform how he designed his training plans.

How did Ralph do it?
Ralph used a 23andMe kit to find out his genetic profile. He researched those genes that have been found to have an impact on fitness to see his body should respond to exercise. For example, did he possess genes that gave him an advantage in building muscle with resistance training? He then modified his training routines to take advantage of this information and monitored his results (using the Polar watch and a Withings scale) to see whether his assumptions held up.

What did Ralph learn?
Ralph found out that he has genetic disadvantages when it came to strength training. This told him that progress in this area depended more on his lifestyle. In particular, he found that eating immediately after working out was important.

When it came to cardio exercise, he had a number of genetic advantages. The unexpected downside to this is that his body adapts quickly to any training regimen, resulting in a plateau. To get around this, he varied his training plan and monitored his results. On one day, he would cycle at a steady rate, while the next, he would use high-intensity intervals. His body seemed to respond to the varied training plan and he hit fewer plateaus. Without knowing which genes he possessed, and reading current research on those genes, it is unlikely that he would have discovered these effective customizations to his training plan.

Ralph has taken what he’s learned and built a tool called Genetrainer to help people use their genetic information to inform their fitness plains. You can check it out here.

Tools: Genetrainer, 23andMe, Polar RCX5, Withings Smart Body Analyzer

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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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Conference Preview: Bill Schuller on Self-Tracking with Children

QSSF13PREVIEW

How will children respond to a world where personal data is ubiquitous? Bill Schuller is starting to find out with his two young children and will be sharing his story at the upcoming 2013 Quantified Self Global Conference.

BillSchullerBill started tracking his exercise and weight in 2010. His preschool-aged son, listening to his father talk about his daily metrics at the dinner table, began to imitate Bill’s tracking behavior, regularly stepping on the scale, not to watch his weight, but to “just check my numbers.” Bill then designed tracking games for him and his son. One of them involved putting things away in the house while tracking steps and gaining “clean-up points.”

This fun talk will feature more stories on the creative ways Bill and his children are playing with self-tracking. As a preview, we have a version of the talk that he gave in San Diego in March 2012. Watch the video and then find out at the conference what further data adventures Bill has had with his kids in the last year and a half.

The Quantified Self Global Conference will be held in San Francisco on October 10th and 11th. Registration is now open. As with all of our conferences, our speakers are members of the community. We hope to see you there!

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Matthew Ames on Stepping on the Scale

We’ve covered weight tracking here many times. It’s a very popular topic, and one of the easiest ways to get started with self-tracking. In this insightful talk from Matthew Ames we learn how weight tracking, in conjunction with diet and activity tracking, positively impact his weight loss and improved his fitness. (filmed at the Boston QS Meetup).

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John Schrom on Locating Weight

John Schrom is a data scientist, graduate student, and avid self-tracker. After taking a look at his historical weight data he decided to dig a bit deeper into the story. Luckily, in addition to collecting his weight (via a Withings scale), he’s also been using Foursquare to collect his geolocation history. With these two data sources in hand he asked himself, “What kind of places do I visit when I’m gaining or losing weight?” Watch this great talk talk recored at the Bay Area QS Meetup to learn how he used association rule mining to explore his data, and what he found. When you’re done with the video make sure to go and read his excellent write-up here.

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Robert Carlsen on Tracking Weight

“I was starting to feel a little bit out of control.”

Robert Carlsen used to be an amateur bike racer. When he moved to New York and stopped racing he found that his weight was slowly creeping up. He was still leading an active lifestyle, but he soon realized that most of daily food choices were the result of guess work. In this video, filmed at the New York City QS Meetup, Robert explains how he used different apps and tools to track his caloric inputs and outputs in order to move towards his goal weight.

Tools:
Body Weight Simulator
Lose It!
Runkeeper
Strava
MobileLogger
Withings Scale + App
Nike Fuelband

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Amelia Greenhall on Using Moving Averages for Maintenance

We’ve posted some great talks by Amelia Greenhall here on the blog and we’re excited to bring you another insightful presentation. Last year Amelia gave a wonderful talk about her weight loss journey and the power of using running averages. In this updated talk Amelia gives a more in-depth look about how using a 10-day moving average serves as an “early warning system” that puts helps put her back on the path of mindful eating. Filmed at the QS Silicon Valley meetup group

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