Tag Archives: fitness
While it is clear that exercise is beneficial, how does one decide what to do to get and stay fit? When Laila Zemrani surveyed people at the gym, she found that a majority don’t decide at all. Sixty percent didn’t know why they were doing a particular exercise. And of those, 50% admitted to merely copying whatever their neighbor was doing.
Laila spoke recently at a QS meetup in Boston about how she tried to be more intentional in her choice in exercise. In reviewing the number of available exercises, she was able to put them into two buckets: strength and endurance. She decided to track the effectiveness of each training regimen by focusing on a single metric and watching its progress. For strength, she focused on body fat ratio. For endurance, she looked out how long it took her to run the same distance. She then alternated her training every three months or so, focusing on one or the other.
Here’s what she found. When she focused on strength training, her body fat ratio improved. For instance, in one three month period it went from 29% to 25%. This type of improvement repeated itself a number of times. However, when she focused on endurance, she did not see improvements in the time it took her to run a certain distance.
It’s hard to know what conclusion to draw from these results. Are these the right metrics for assessing performance? What does it mean to respond more to strength than endurance exercise? However, the question of why Laila seemingly responds better to strength-based exercises may be found in her genetics. She used a DNA test from 23andMe and the results suggested that she shows a propensity toward building fast-twitch fibers which allow for better performance at explosive activities, such as sprinting or weight-lifting. On the flip side, people who are more proficient at building slow-twitch fibers tend to do better at endurance-type activities such as running long distance. Everyone has a combination of the two types of muscle fiber, but the ratio seems to be correlated with performance, depending on the type of activity.
With these results, Laila decided it made sense for her to focus on strength-building exercises, since it seems that her body was built for that type of activity. Laila feels that having this information is allowing her to personalize her regimen and be more intentional about how she exercises, rather than be too influenced by the latest fads in fitness.
It can be debated whether it makes sense to focus on strength as opposed to endurance, depending on which one you see progress in. For Laila, the appearance of progress is important psychologically, in that it is easier to motivate herself if she sees improvement. There could be a downside to appearance of quick improvement, though. Ralph Pethica also uses genetic data to inform his training. He is the opposite of Laila in that his body is better suited for endurance exercise. What he finds, though, is that he improves and adapts too quickly and sees his performance plateau. To overcome this, he found that switching between steady-state training sessions and high-intensity intervals minimized the time he spent plateaued.
Training with knowledge of your genetic background is still a nascent practice. It’s still unclear how this information can and should be used. Useful ways to take advantage of this genetic information is still being tested and developed, but progress could be hastened if more people knew if they had more slow-twitch or fast-twitch muscle fiber. If this awareness is increased, it could lead to better strategies to get more out of exercise and reduce frustration and, hopefully, abandonment of the gym.
Fitbit Aria Wi-Fi Smart Scale
QS17 Tickets are Available
Our next conference is June 17-18 in lovely Amsterdam. It’s a perfect event for seeing the latest self-experiments, debating the most interesting topics in personal data, and meeting the most fascinating people in the Quantified Self community. There are only a few early-bird discount tickets left. We can’t wait to see you there.
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.
A short list this week. Enjoy!
How Networks Bring Down Experts by Max Borders. Max gets double points for this great piece on using networks and peer-to-peer learning for developing personal expertise. Loved the reference to the writing of Michael Polanyi.
Mark Cuban on Blood Testing- Drawing the Wrong Conclusion or a Step in the Right Direction? by Bruce Williams. A nice piece by Dr. Williams about the recent controversy over patient generated blood testing brought on by Mark Cuban.
Defining a New Indicator of Cardiovascular Endurance and Fitness by Marco Altini. Marco has been exploring fitness and heart rate variability detection using iOS applications. Recently he’s been using activity and HRV to examine a new method for determining fitness level. As per usual, Marco wrote an amazing and in-depth report using his own data to showcase what he’s learning from his new application.
Quantified Self: A Data Visualization by Joyce Chow, Kinan A, and Adam S. Three students explored data visualization and self-tracking through logging diet and activity.
From the Forum
In our first episode of QS Radio we hit the ground running with a great pair of interviews and some super interesting news and discussion about exciting self-tracking projects.
In our show&tell segment, we hear from Shannon Conners, a self-tracking enthusiast who’s been learning amazing things from tracking her diet, exercise, and weight for over four years. Jessica Richman, CEO and co-founder of uBiome, joins us for a short Toolmaker Talk where we learn about the importance of the microbiome and citizen science. To wrap up, Ernesto and Steven share a few interesting tech and self-tracking stories in a segment we call “What We’re Reading.”
We hope you enjoy this inaugural episode. Make sure to check the show notes below for links to items we discussed.
Download the episode here or subscribe on iTunes.
You can find out more about Jessica Richman and uBiome on their website.
What We’re Reading
Siva Raj was interested in lowering his blood pressure. With a family history of cardiovascular disease and heart attacks he was worried about slightly elevated blood pressure (pre-hypertension). As someone engaged with understanding and building fitness applications he thought he would be able to lower his blood pressure by staying on track with a regular exercise program that focused on cycling. Interestingly his blood pressure measurement didn’t respond to his constant exercise or weight loss. After reading more research literature about the link between fitness and cardiovascular health Siva decided to change his training to improve his fitness. He decided to incorporate a increased intensity into his routine. After a short period of time he had increases in this fitness and was able to observe the reduction in blood pressure he was looking for. In the video below, filmed at the Boston QS meetup group, Siva explains his methods and talks about how he was able to track his body’s response to different fitness routines.
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
We hope you enjoy this weeks list. Feel free to submit articles, show&tell self-tracking stories, and QS data visualizations. Just email me!
Why can’t you track periods in Apple’s Health app? by Nat Buckley. With the recent re-release of Apple’s HealthKit enabled self-tracking and personal data system it no wonder that people are taking a long hard look at what data is being excluded. With the popularity of menstruation tracking apps (this app has nearly 30,000 ratings) it’s surprising this was overlooked. This excellent post is a must read on the topic.
Now That Cars Have Black Boxes, Am I Being Tracked? by Popular Science Editors. Questions and concerns about surveillance are becoming more commonplace. As someone who is looking to purchase a car in the next year or so I was happy to see this post come across my stream.
The Quantified Self community, lifelogging and the making of “smart” publics by Aristea Fotopoulou. I love it when people take a thoughtful look at the Quantified Self community and write about their experiences:
For me, the potential of QS for public participation lies in the show and tell meet-ups that constitute a central feature of this community. Meet-ups enable the exchange of stories about the success or failure of lifelogging practices; they allow people to connect and form synergies around common interests, and to explore wider questions such as personal data management and ownership. [...] members touch upon key political issues and create temporary spaces of dialogue: what happens to personal data, who has access to these data (is it private individuals, governments or corporations)? For what purposes (medical research)? And how can these data be interpreted (by algorithms, visualisations) and used to tell stories about people?
Stepping Down: Rethinking the Fitness Tracker by Sara M. Watson. Sara uses her personal journey of recovery from hip surgery to frame an interesting question: Should we trust our fitness trackers to prescribe movement goals?
Practical Statistical Modeling: The Dreaded After-School Carpool Pickup by Jamie Todd Rubin. Jamie wanted to understand if there was a way he could reduce how much time he spent waiting in line to pick up his son from school. Why not track it and model it!
Bulletproof Diet and Intermittent Fasting: 1.5 Year Results by Bob Troia. Bob takes a deep dive into his data to see if this particular diet is having beneficial health effects. Click for the great data, stay for the wonderful discussion and very, very thorough write-up.
Quotidian Record by Brian House. I’ve been a fan of Brian House since his early days visualizing Fitbit data. I was reminded of this work during a conversation about geolocation data and thought it would be a nice addition to our visualization list.
Visualizing My Daily Self-Management by Katie McCurdy.
What does my daily medication and self-management look like? How could I visualize this regimen? How can I communicate the ‘burden’ and work of caring for myself?
I decided to draw pictures of the things that I need to do on a daily basis; that way I could show the workshop attendees what my day was like instead of just telling them.
It’s Time to Eat by Karl Krehbiel. Karl, a data science intern at Jawbone used the data from their global community of users the determine the likelihood of food and drink consumption during the day. Really fun and interesting visualizations here.
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.
Bill 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!
Bill Schuller started tracking his exercise and weight in 2010, and got into the habit of talking about his numbers each night at the dinner table. Before long, his kids got interested in tracking too. In the video below, Bill talks about what he learned and tells some fun stories, including one about a tracking game he made up with his five-year-old son to clean up the house while his wife was away for the weekend. (Filmed by the San Diego QS Show&Tell meetup group.)
Andy Leigh wanted to row around the world from his bedroom. Why? To lose weight and to do some kind of project with the open source hardware Arduino. He chose rowing because it’s a low-impact activity that he can do with his injury. But manual tracking in a spreadsheet was too cumbersome. In the video below, Andy walks through his hardware hacking in fascinating detail, and reveals his route around the world, which he is plotting on a Google map as he goes. (Filmed by the London QS Show&Tell meetup group.)