Search Results for: weight

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 ouse expert 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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Meetups This Week

There are a stellar collection of meetups going on this week. 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!

Tuesday (September 2)
Geneva, Switzerland
The Geneva group will feature a show&tell about tracking weight-loss alongside Basis Band data.

Wednesday (September 3)
Oslo, Norway
The great Oslo group will be having their fourth meeting.

Thursday (September 4)
Berlin, Germany
The Berlin group is adopting a workshop format this week to talk about habit formation.

Cologne, Germany
The Cologne group has a packed program with talks on happiness, healthcare, and cryonics.

Sunday (September 7)
Lincoln, Nebraska
The Lincoln group has a great program that will cover measuring ketosis, the effect of antioxidants on migraines, tracking sleep, and using DNA to inform fitness plans.

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What We Are Reading

Enjoy this week’s list!

Articles
Effect of Self-monitoring and Medication Self-titration on Systolic Blood Pressure in Hypertensive Patients at High Risk of Cardiovascular Disease by Richard McManus et al. An interesting research paper here about using self-monitoring to reduce blood pressure. The paper is behind a paywall, but since you’re nice we’ve put a copy here.

Apple Prohibits HealthKit App Developers From Selling Health Data by Mark Sullivan. Some interesting news here from Apple in advance of their new phone and possible device release in a few weeks. I applaud the move, but would like to see more information about data portability in the next release.

Science Advisor, Larry Smarr by 23andMe. Great to hear our friends 23andMe and Larry Smarr are getting together to help work on understanding Inflammatory Bowel Disease. If you’ve been diagnosed with Crohn’s disease or ulcerative colitis consider joining the study.

Personal Health Data: It’s Amazing Potential and Privacy Perils by Beth Kanter. A lot of people have been talking recently about the privacy implications of using different tracking tools and technologies. In this short post Beth opens up some interesting questions about why we might or might not open up our personal data to others. Make sure to read through for some insightful comments as well.

Show&Tell
Let’s Talk About 3 Months of Self-Quantifying by Frank Rousseau. Frank is one of the founders of Cozy Cloud, a personal could service. He’s also designed Kyou a custom tracker system built on top of Cozy. He’s also been using the services to track his life. In this post he explain how tracking his activity, sleep, weight, and other habits led to some interesting insights about his behavior.

The iPhone 5S’ M7 Predictor as a Predictor of Fitbit Steps by Zach Jones. A great post here by Zach as he explores the data taken from his iPhone 5S vs. his Fitbit.

Using Open Data to Predict When You Might Get Your Next Parking Ticket by Ben Wellington. Not strictly a personal data show&tell here, but as someone who suffers from street sweeping parking tickets somewhat frequently I found this post fascinating. Now to see if Los Angeles has open data…

Visualizations
RWTime
What Time of Day Do People Run? by Robert James Reese, Dan Fuehrer, and Christine Fennessay. Runners World and Runkeeper partnered to understand the running habits of runners around the world. Some interesting insights here!

FitbitMin
What Happens When You Graduate and Get a Real Job by Reddit user matei1987. A really neat visualization of min-by-min level Fitbit step data.

DataDesign
Data + Design by Infoactive and the Donald W. Reynolds Institute. A really interesting and unique take on a data visualization book. This CC-licensed, open source, and collaborative project represents the work of many volunteers. I’ve only read through a few chapters, but it seems to be a wonderful resource for anyone working in data visualization.

From the Forum
Good Morning World!
Quantified Chess
New Activity Tracker to Replace BodyMedia?
Indirect Mood Measures
OPI TrueSense for Sleep Tracking

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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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Mark Leavitt: Whipping up My Willpower

When we decide to track one thing, we sometimes find that we are indirectly tracking something else.  That is the theme of today’s talk.

When Mark Leavitt was 57, he found out that he had heart disease, a condition that runs in his family. Mark set about making some life changes. He tracked his weight while adopting a low-fat diet. His tracking showed him that he was making progress and that progress encouraged him to keep tracking. But once Mark’s weight loss stalled and then started to backslide (though he had maintained his diet) his desire to track dwindled and was then snuffed out by a major life event.

Though he was ostensibly tracking weight, this experience gave him some insight into his motivation. He began to build a mental model of his willpower. When was it strong? When was it weak? Using his background as a doctor to make assumptions on the nature of his willpower, he used the tracking of other lifestyle changes, such as movement and strength-training, to test those assumptions and better understand how to follow through on his intentions.

Watch below to see what Mark found worked for him and if you would like to see how Mark’s keeping up with his habits, you can check out his live dashboard here.

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Mark Drangsholt: Deciphering My Brain Fog

One of the benefits of long-term self-tracking is that one builds up a toolbox of investigatory methods that can be drawn upon when medical adversity hits. One year ago, when Mark Drangsholt experienced brain fog during a research retreat while on Orcas Island in the Pacific Northwest, he had to draw upon the self-tracking tools at his disposal to figure out what was behind this troubling symptom.

Watch this invaluable talk on how Mark was able to combine his self-tracking investigation with his medical treatments to significantly improve his neurocognitive condition.

Here is Mark’s description of his talk:

What did you do?
I identified that I had neurocognitive (brain) abnormalities – which decreased my memory function (less recall) – and verified it with a neuropsychologist’s extensive tests.  I tried several trials of supplements with only slight improvement.  I searched for possible causes which included being an APOE-4 gene carrier and having past bouts of atrial fibrillation.

How did you do it?
Through daily, weekly and monthly tracking of many variables including body weight, percent body fat, physical activity, Total, HDL, LDL cholesterol, depression, etc.   I created global indices of neurocognitive function and reconstructed global neurocog function using a daily schedule and electronic diary with notes, recall of days and events of decreased memory function, academic and clinical work output, etc.  I asked for a referral to a neuropsychologist and had 4 hours of comprehensive neurocog testing.   

What did you learn?
My hunch that I had developed some neurocognitive changes was verified by the neuropsychologist as “early white matter dysfunction”.  A brain MRI showed no abnormalities.  Trials of resveratrol supplements only helped slightly.   There were some waxing and waning of symptoms, worsened by lack of sleep and high negative stress while working.  A trial with a statin called, “Simvastatin” (10 mg) began to lessen the memory problems, and a dramatic improvement occurred after 2.5-3 weeks. Subsequent retesting 3 months later showed significant improvement in the category related to white matter dysfunction in the brain.  Eight months later, I am still doing well – perhaps even more improvement – in neurocog function.

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Steven Jonas: Memorizing My Daybook

Memory, cognition, and learning are of high interest here at QS Labs. Ever since Gary Wolf published his seminal piece on SuperMemo, and it’s founder Piotr Wozniak, in 2008, we’ve been delighted to see how people are using space repetition software. Our friend and colleague, Steven Jonas, has been using SuperMemo since he read Gary’s article and slowly transition to daily use in 2010. Steven has been quite active in sharing how he’s used it to track his different memorization and learning projects with his local Portland QS meeup group. At the 2014 Quantified Self Europe Conference, Steven introduced a new project he’s working on, memorizing his daybook – a daily log he keeps of interesting things that happened during the day. Watch his fascinating talk below to hear him explain how he’s attempting to recall every day of this life. If you’re interested in learning more about spaced repetition we suggest this excellent primer by Gary.


You can also download the slides here.

What did you do?
I used a spaced repetition system to help me remember when an entry in my daybook occurred.

How did you do it?
Using Supermemo, I created a flashcard each morning. On the question side, I typed what I did the previous day. On the answer side, I typed down the date. SuperMemo would then schedule the review of these cards. I also played around with adding pictures and short videos from that day to the card, as well.

What did you learn?
First, that this seems to work. I’ve built up a mental map of my experiences, unlike anything I’ve ever experienced. I also learned that I hardly ever remember the actual date for a card. Instead, it’s a logic puzzle, where I can recall certain details such as, “It was on a Saturday, and it was in October, the week before Halloween. And Halloween was on a Thursday that year.” From there, I can deduce the most likely day that it occurred. I’m also learning which details are most helpful for placing a memory. Experiences involving other people and different places are very memorable. Noting that I started doing something, like “I started tracking my weight”, are not memorable.

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QSEU14 Breakout: Families and Self-tracking

Today’s post comes to use from our friend and co-organizer of the Bay Area QS meetup group, Rajiv Mehta. Rajiv and Dawn Nafus worked together to lead a breakout session that focused on self-tracking in the family setting at the 2014 Quantified Self Europe Conference. They focused on the role families have in the caregiving process and how self-tracking can be used in caregiving situations. This breakout was especially interesting to us because of the recent research that has shed a light on caregivers and caregiving in the United States. According to research by the Pew Internet and Life Project, “39% of U.S. adults are caregivers and many navigate health care with the help of technology.” Furthermore, caregivers are more likely to track their own health indicators, such as weight, diet and exercise. We invite you to read the description of the breakout session below and then join the conversation on the forum.

Families & Self-Tracking
by Rajiv Mehta

In this breakout session at the Amsterdam conference, we explored self-tracking in the context of family caregiving. In the spirit of QS, we decided to “flip the conversation” — instead of talking about “them”, about how to get elderly family members to use self-tracking technologies and to allow us to see their data, we talked about “us”, about our own self-tracking and the benefits and challenges we have experienced in sharing our data with family and friends. These are the key themes that emerged.

Share But Not Be Judged
Feeling like you’re being judged, and especially misjudged, by someone else seeing your data is a very negative experience. People want to feel supported, not criticized, when they open up. Ironically, people felt that reminders and “encouragement” by an app, knowing that it is based on some impersonal algorithm, was sometimes easier to accept than similar statements from family. The interactions we have with family members aren’t neutral “reminders” to do this or that; they’re loaded with years of history and subtext. One participant commented “What I really want is an app that trains a spouse how not to judge.”

Earn The Right
So much is about learning how to earn the right to say something—that’s an ongoing negotiation, and both people and machines have to earn this. Apps screw it up when they try to be overfamiliar, your “friend.” I recalled a talk from the 2013 QS Amsterdam conference of a person publicly sharing his continuous heart rate monitoring, whose boss had noticed that the person’s heart rate had not gone up and demanded to know why he was not taking a deadline seriously! Such misjudgments can kill one’s enthusiasm for sharing.

Myth Of Self-Empowerment
Just because you’re tracking something, and plan to stick to some regimen or make some behavioral change, doesn’t mean you’re actually empowered to make it so. Family members need to be sensitive to the fact that bad data (undesirable results, lack of entries, etc.) may be a “cry for help” rather than an occasion for nagging.

Facilitating Dialog and Understanding
On the positive side, sharing data can lead to more understanding and richer conversations amongst family members. One participant described his occasional dieting efforts, which he records using MyFitnessPal and shares the information with his mother. This allows her to see how he is able to construct meals that fit the diet parameters (and so learn from his efforts), and also to just know that he is eating okay. I described the situation of a friend with a serious chronic disease who was tracking her energy levels throughout the day. In considering whether or not to share this tracking with her family she realized that they had very little appreciation of how up-and-down each day is for her. So, before she’s going to get benefits from sharing continuous energy data, she’s going to have to help her family understand the realities of her condition.

Sense of Control
Everyone felt that one key issue was that the self-tracker feel that s/he is the one making the decision to share the data, and has control over what to share, when to share, and who to share with.

We hope that before people design and deploy “remote monitoring” or “home tele-health” systems to track “others”, they first take the time to share their own data and see what it feels like.

If you’re interested in reading further about technology and caregiving we suggest the recently published report from the National Alliance for Caregiving, “Catalyzing Technology to Support Family Caregiving” by Richard Adler and Rajiv Mehta.

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Steven Dean: A Quantified Sense of Self

At our 2014 Quantified Self Europe Conference, as with all our events, we sourced all of our content from the attendees. During the lead up were delighted to have some amazing interactions with attendees Alberto Frigo and Danielle Roberts, both of whom have been engaged with long-term tracking projects. This theme of “Tracking Over Time” was nicely rounded out by our longtime friend and New York QS meetup organizer, Steven Dean. Steven has been tracking himself off and on for almost two decades. In the talk below, Steven discusses what led him to self-tracking and how he’s come to internalize data and experiences in order to create his sense of self.

Transcript
Quantified Sense of Self
by Steven Dean

Twenty years ago, I was in grad school getting an MFA. I was making a lot of objects that had very strong autobiographical component to it. Some I understood the source of. Many I did not. Continue reading

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What We're Reading

Enjoy this week’s list!

Articles
CGM in the Cloud: Personal Preferences by Kerri Sparling. A great blog post here by Kerri who explains why it’s so important to have access to her blood sugar data. She’s part of a growing community of people with diabetes who are using different methods to broadcast their CGM data into the could.

On Minorities and Outliers: The Case for Making Big Data Small by Brooke Foucault Welles. The rush towards finding the answers in “Big Data” might lead to the continued exclusion of the women, minorities, and the “outliers” of the world. Brooke makes the case here for examining these “small datasets”  to give them the weight they deserve.

“When women and minorities are excluded as subjects of basic social science research, there is a tendency to identify majority experiences as “normal,” and discuss minority experiences in terms of how they deviate from those norms . In doing so, women, minorities, and the statistically underrepresented are problematically written into the margins of social science, discussed only in terms of their differences, or else excluded altogether.”

Here’s Looking at You: How Personal Health Information Is Being Tracked and Used [PDF] by Jane Sarashon-Kahn. In this report, from the California Healthcare Foundation, Jane lays out how our health data is being acquired and used, for commercial and public benefit. I especially liked the emphasis on privacy, or lack there of.

The Making of April Zero by Anand Sharma. Anand details his journey from starting to self-track to creating an amazing website that serves as his personal QS dashboard. One interesting bit is that his tracking activities increased dramatically after Apple’s M7 chip came out with the iPhone 5S and he noticed that his phone’s battery took much less of a hit from running apps that track his activity in the background.

Show&Tells
Tracking Upset and Recovery by Paul LaFontaine. Paul has been using the Heartmath stress monitor to help him record and understand what causes him to get upset (fall out of coherence). In this post, he details how his recovery method has helped him progress, recover, and slightly reduce the number of upsets during his working session. I recommend reading all of Paul’s great posts on this work.

Europe Honeymoon by reddit user Glorypants. This reddit user tracked his European honeymoon with the Moves app and then used our How to Map Your Moves Data post to learn how to make some great maps to share his experience.

Visualizations
Lillian_YIR
This Year in Numbers – 2014 by Lillian Karabaic. A great “year in review” post here that details the tracking Lillian has done from July 2013 to July 2014. I love the mix of hand-drawn and computer-generate visualizations that provide insight into Lillian’s sleep, diet, cycling, mood, and communication data. (Editor’s Note: Lillian sent this link via the comments on Quantifiedself.com. If you have something to share please let us know!)

HelpMeViz
HelpMeViz.com. I wanted to highlight this great website and community project as we have many great visualization and data scientists in our community. On the HelpMeViz website people submit their visualizations for feedback and assistance. I’ve had fun interacting with the growing community and have even learned a few neat tricks in the process.

TravisHodges
The Quantified Self by Travis Hodges. Travis is a portrait photographer based in London. For his newest project he sought out fifteen individuals who are using self-tracking to understand and improve themselves. I especially like the inclusion of the data visualizations coupled with the individual stories from these self-trackers.

TwitterViz
Visualizing Your Twitter Conversations by Jon Bulava. Jon, a Developer Advocate at Twitter, put together a wonderful how-to for getting started on visualizing your friend network on Twitter. (If you’re interested in using the new Twitter Analytics data to better understand your tweeting we suggest Bill Johnson’s great how-to.)

From the Forum
Data Aggregation
Smart Mirror with Health Sensors
Garmin Vivo Activity Tracker – Your Results?
Sleep Tracking for New Parents

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