Tag Archives: sleep
Eric Jain stumbled upon a study published in 2013 that found the a full moon was associated with less sleep. Being an avid self-tracker and a toolmaker he decided to find out if that was true for him as well. Eric used his tool, Zenobase, to import, aggregate, filter, and then analyze his sleep data in a few unique ways. While he found some evidence that a full moon was associated with less total sleep he wasn’t able to make any statistically significant results. Watch his short video below, filmed at the Seattle QS meetup group, then take a look at his great screencast where he walks through all his steps to complete this analysis.
This guest post comes to us from Mark Moschel and Eugene Granovsky, the co-organizers of the Chicago Quantified Self meetup group. At their recent meetup on March 26, 2014 they had three great talks from community members. If you live in the Chicago area why not join the group!
Dan Abreu on GeoTracking
Dan travels a lot. I mean… a LOT! He stepped through an airport well over 300 times in 2012. He started documenting his travel a few years back and has used a variety of tools since: TripIt, Track My Life (discontinued), Google Latitude (discontinued), QStartz, and myTracks. During that time, his technique for tracking evolved and gained complexity. He’s now able to develop very detailed maps of his trips (see below). What has he learned from all this? “Not much” he said. However, he enjoys the practice and consistency of it and is excited to continue finding more uses for this data in the future.
Zak Boswell on Sleep
Like many of us, Zak was on a very inconsistent sleep schedule for most of his life and would often stay up too late. However, unlike many of us, Zak was experiencing severe fatigue during the day. In the span of just a couple years, he had 4 car accidents from falling asleep at the wheel (in two, his car was totaled). Realizing this was a problem, he started exploring traditional solutions. He saw a handful of doctors and participated in a very expensive (and ineffective) sleep study. During this time, he also started tracking his sleep and decided to go to bed at a consistent time each day (around midnight). In the data, he saw his sleep quality beginning to improve. He also stopped falling asleep during the day. At first, he struggled with the change, but he’s since changed his whole philosophy and loves it. You can view Zak’s presentation here [PDF].
Ovetta Sampson on how tracking helped her become an Ironman (or “The science of Faith”)
Let’s start with the end on this one. Here’s what Ovetta accomplished: 2.4 mile swim, 112-mile bike ride, 26.2 mile run – all in under 17 hours. Wow! Even more impressive is that she was never an athlete growing up and weighed 270 lbs in 2012. In just a year, she turned a seemingly impossible goal into a real accomplishment. How? She found faith in her data. “Tracking data helped me change my behavior” she said. By tracking her times, weight, speed, and distance, a few things happened: 1) she quickly saw progress and was motivated to keep going, 2) she became competitive with herself, always trying to beat her last score, and 3) she could ignore the thoughts in her mind. As she said, “you have to trust something and the mind is not to be trusted. Trust the data.” Her thoughts kept telling her to quit, but the data proved she was doing well. She didn’t quit and now she’s an Ironman. You can view Ovetta’s presentation here [PowerPoint].
For those of you in the Chicago area Elmhurst Art Museum is hosting a new exhibit called “Lifeloggers: Chronicling the Everyday.” Check it out here.
“If I look at this, I have these memories, and I remember this was a good year.”
Collect it and forget it. This could be be hidden mantra of many people engaged with self-tracking, myself included. I will readily admit to buying a device or application with the hope that I can collect enough information to generate a grand insight at some mythical point in the future where the intersection of free time, analytical knowledge, and sample size magically coalesce. Ulrich Atz encountered the same problem. He was tracking, but soon lost sight of the purpose. Rather than giving up he started a new tracking project.
Ulrich started by building on the popular habit and tracking theory, Don’t Break the Chain, based on consistency in behaviors you care about. He identified six major categories he wanted to understand and pay attention to: his evening ritual, fitness, nutrition, learning, sleep, and travel. Rather than using an passive tracking system like Foursquare of Sleep Cycle, he decided to keep track of it by writing on a large wall calendar. In this presentation, given at the London QS meetup group, Ulrich describes his methods and what he learned from this year-long process.
Even in a world of connected devices, wearable technology, and near ubiquitous data connections self-tracking and personal data collection can be difficult endeavor. Aaron Parecki has been tracking various aspects of this life for years – specifically location, weight, and sleep. We’ve covered some of Aaron’s work and his amazing geolocation visualizations here before and we were excited to have him speaking about his experiences at our 2013 Global Conference. Watch this fantastic talk to hear about Aaron’s tracking practices and his thoughts on why a personal data server is an important tool.
Update: Aaron let us know that his slides from this talk are also available and can be viewed here.
We’ll be posting videos from our 2013 Global Conference during the next few months. If you’d like see talks like this in person we invite you to join us in Amsterdam for our 2014 Quantified Self Europe Conference on May 10 and 11th.
This is concatenation of screenshots from my sleep app. Most sleep apps don’t let you zoom out like this and still see daily/nightly detail, so I just made it myself. I like that it shows how almost-consistent I am with my sleep, and made me ask new questions about the “shape” of a night of sleep for me.
Tool: Azumio Sleep Time
We invite you to take part in this project as we share our favorite personal data visualizations.If you’ve learned something that you are willing to share from seeing your own data in a chart or a graph, please send it along.
This guest post comes to us from Konstantin Augemberg who covers many interesting Quantified Self topics and his personal tracking experience on the wonderful MeasuredMe blog.
On Monday, September 30, Quantified NYC group has held its 23th meetup. The event was graciously hosted by Projective Space which offers collaborative community space to over 60 startups. With over a hundred people in attendance, interesting demos and inspiring presentations (quantifying Starcraft gaming skills, predicting choice of clothes based on weather forecast, and other self-quantified awesomeness!), it turned out to be a great evening. Here is my brief report on what I saw and loved:
We started with our Demos session during which QS entrepreneurs showcased their products and services:
- David Joerg (@dsjoerg) presented his GGTracker, web service that uses advanced analytics to help Starcraft players to track their stats and quantify and improve gaming skills
- Paula Murgia presented Personal Beasties app that helps people to cope with anxiety, fatigue and stress by using simple breathing exercises
- Stefan Heeke (@Stefan_Heeke) showcased My Online Habits, a webapp that uses Gmail and Google data to help analyze your productivity and communications habits
- Mike McDearmon (@Mike_McDearmon) demoed an awesome online dashboard that he built to visualize his outdoors activities.
The Show & Tell session was opened by Mette Dyhrberg (@mettedyhrberg) and her “The Pomodoro Recovery” presentation. Following the bouncing castle accident, Mette has been diagnosed with concussion and was recommended to rest and avoid using electronic devices in order to recover. She started tracking her symptoms, diet, and resting and working habits using Pomodoro method and Mymee app. The lack of progress has prompted her to look at her tracking data, after which she realized that she may have been misdiagnosed. The visit to another doctor has revealed that she sustained a neck injury, which luckily, could be fixed right on the spot. The treatment procedure helped her to feel better almost immediately. You can watch Mette’s presentation here.
In “Quantifying What to Wear”, Andrew Paulus (@andrewcpaulus) shared how he used self-tracking to measure impact of weather on his choice of clothes. It started when Andrew noticed that one of his morning habits included checking weather on his phone in order to decide what to wear on that day. That led to an idea to measure efficiency of this process, by tracking his choice of clothes and then assessing at the end of the day, if the choice was correct. His first attempt at quantifying weather and wardrobe was unsuccessful, due to some flaws in methodology and measurement (e.g., the weather data was collected at different times of the day; the clothes data was not very well structured). Andrew then has revised the methodology, by subscribing to more reliable and comprehensive weather data from Farmer’s Almanac, and logging wardrobe data in a more consistent manner. His girlfriend kindly agreed to co-participate in this experiment. After six months of tracking, Andrew looked at their data. He found that the overall, he tended to be slightly more accurate in choosing what to wear, compared to his girlfriend: his accuracy rate was 78%, vs. her rate of 74%. Another interesting finding was that his choices were more weather appropriate. The correlation between the clothes and weather was nearly 0.7 for him, and nearly 0 .1 for his girlfriend, which suggests that her choices are often influenced by many other factors, not just weather. You can see the full presentation here.
Amy Merrill (@amyjmerrill) shared her experiences with “Sleep Tracking with Jawbone Up”. Since April 2013, she has been tracking her sleep (deep sleep phase, in particular) using Jawbone Up, as well as social and work related activities using Google Calendar. By analyzing the patterns in her data, she was able to see how certain activities affect her deep sleep. In particular, she learned that more physical activity and sleep deprivation led to more deep sleep, where as restful days tend to result in more light sleep. Certain social activities like attending wedding and taking trips on tour bus have also had a considerable impact on quality of her sleep. For the next phase, she plans to include some aspects of the diet, including consumption of alcohol, caffeine and over-the-counter drugs. You can watch Amy’s presentation here.
The session was concluded by Andrew Tarvin’s (@HumorThatWorks) funny and inspiring presentation “The Perfect Day”, in which he discussed the tracking system that he used to build some new habits. Andre has been rating each day based on the number of goals that he achieved (e.g., waking up without snoozing the alarm, do something active for 20+ minutes, eat at least 4 fruites a day, etc.) The days with at least 3 goals met were defined as “quality days”, and the days with all 5 goals accomplished were rated as “perfect”. Andre learned that the strive for perfection was the most demotivating factor: missing one goal earlier in the day often resulted in giving up on all other habits as well. Waking up without snoozing was the most influential habit in that regard. He also learned that the “streaks” of quality and perfect days was the most motivational factor; once he had several consecutive successful days in a row, it was much easier to continue meeting the goals. Andre has been using this system for three years, and plans to continue using it to acquire new habits. You can read more about his system on his site. You can watch video of the presentation here.
As always, before and after the sessions, I had a chance to mingle and meet a lot of interesting people. Special shout out to Stefan Heeke, Mike McDearmon, Sylvia Heisel, Michael Moore and Dave Comeau.
If you’re a loyal, or even infrequent user of the Zeo sleep tracking device then you’ve probably heard the sad news that the company has shut down. This opens up a lot of questions about what is means to make consumer devices in this day and age, but rather than focus on those issues we’ld like to talk a bit about data.
Zeo has been unfortunately a little quiet on the communication front and there are quite a few users out there who are wondering about what will happen to all those restless nights and sound sleeps that were captured by their device. This has been compounded by the fact that the Zeo website went down for a short time (it is up as of this writing) closing off access to user accounts and the data therein. Lucky for you there have been quite a few enterprising and enthusiastic individuals who have taken the time to create or highlight ways to capture and store your Zeo data.
Use The Zeo Website
You can’t fault Zeo with making it hard to access your own data. As long as their website is up you can easily download your sleep data from by logging into your user account at mysleep.myzeo.com. After logging into your account you will see a link on the right hand side labeled “Export Data.” Click that link and you’ll be able to download a CSV file containing all your sleep data. They’ve even provided a description of the data and formats that you can download here.
Eric Blue’s FreeMyZeo Data Exporter
QS Los Angeles Meetup Organizer and hacker extraordinaire whipped up a simple data export tool using the Zeo API. The great thing about Eric’s is that even if the myZeo web portal goes down this tool should continue to work.
Download Data Directly From the Device
If you’re using a Zeo bedside device then you can continue to use it and download the data directly from the memory card without relying on uploading it to the Zeo website. In order to do this you’ll have to read the documentation and use the Data Decoder Library. These files are hard to find as they’ve been removed from the Zeo developer website, but you can access them from our Forum thanks to our friend Dan Dascalesu. Zeo also created a viewer using this library that you can use via this Sourceforge page.
If you’ve found another way to download Zeo data please let us know. You can also participate in the great forum discussion that inspired this post.
At its core, Quantified Self is a community-driven effort to extract personal meaning from personal data. Our conferences reflect that by providing opportunities to learn what others are doing in their Quantified Self practice. Through our Show & Tell presentations you get to see first-hand accounts of how data is being collected and put to use in order to understand and investigate personal phenomena, but that’s not all our conference have to offer. In the spirit of collaborative learning we also schedule “Breakout Sessions” alongside our wonderful Show & Tell talks. These sessions, like all our conference programming, are developed and and facilitated by our wonderful attendees. Here’s a preview of just a few of the many fantastic Breakouts we have scheduled.
Title: The Self in Data
Breakout Leader: Sara Watson
Description: In my research on the QS community, I’ve found that we talk a lot about our technical requirements of data, and about how we want to use data. What we don’t often talk about is what it means to know ourselves through data. This breakout is an opportunity to discuss what data tells us about ourselves and how we relate to our data.
Title: On Sleep Tracking
Breakout Leader: Christel De Maeyer
Description: Does self-monitoring with devices like myZeo, Body Media create enough awareness and persuasion to change behavior and to maintain new habits? We would like to use this session to learn and share our experiences.
Title: Tracking breathing as a Unifying Experience
Breakout Leader: Danielle Roberts
Description: During this session we can exchange experiences on the tracking of respiration and tracking and visualising of life group data in general. You’ll have the opportunity to take part in a demo using custom breath tracking wearables and real time visualisation of breath data.
Title: Activity trackers
Breakout Leader: Michael Kazarnowicz
Description: We’ll take a look at the most common activity trackers on the market today. We will look at the trackers (maybe even play around with them hands-on) and compare the functions and the data you can get from them.
Title: QS as a Catalyst for Learning?
Breakout Leader: Hans de Zwart
Description: In this session we will explore whether quantifying yourself can act as a catalyst for learning. Can it speed up the learning process? Can it help us in achieving the holy grail of learning, a personalized tutor? What perverse effects might it have in the context of learning?
The Quantified Self European Conference will be held in Amsterdam on May 11th & 12th. Registration is now open. As with all our conferences our speakers are members of the community. We hope to see you there!
Ari Berwaldt wanted to better understand how his sleep affected his mental performance. In this great talk Ari explains his insights from tracking his cognitive skills using Quantified Mind and some surprising results about the lack of correlation between his Zeo data and his mental performance. Make sure to keep watching as Ari also explains some very interesting data and conclusions from blood glucose and ketone tracking during fasting. Filmed at the QS Silicon Valley meetup group.
Jules Goldberg is a snorer, and estimates that he has spent 1/8th of his life snoring. The noise was bothering his wife, so he built an app called SnoreLab to quantify his snoring (mild, loud, or epic?) and help him reduce it. In the video below, Jules shares how he identified where his snoring was coming from, remedies he tried, and which ones made it better and worse. (Filmed by the London QS Show&Tell meetup group.)