Tag Archives: bayarea
With all the self-tracking applications, devices, and services out there it can be hard to make sense of all the data you’re collecting. Anand Sharma ran into this situation in 2014 when he started thinking about his data and how he wanted to use it to help him understand himself, optimize what he cared about, and help him tell the story of his life through data. He tackled this problem by creating a personal website called Aprilzero that let him publicly expose his data and insights. After a large influx of positive feedback Anand, along with a few collaborators, has launched Gyroscope, which enables individuals to use his visualization and aggregation system. We were excited to have Anand at our Bay Area meetup group a few months ago, where he told us the story of hw this all came together and what he’s been learning in the process.
To learn more about Anand, and his journey to create Aprilzero and Gyroscope check out his journal.
How many times during the course of the day do you find your mental state drifting into negativity, feeling like you’re lost, or just plain stressed? How could you even keep track of this, and why would you want to?
What Did Paul Do?
Paul LaFontaine has been tracking what he calls “upsets” to better understand himself, the way he works, and to see if he can improve his mental and physiological response and recovery.
Upsets are something physiological that were happening beneath the surface, and they’re trackable. It didn’t have to be emotional, but there had to be a signal. This project is part of an longer ongoing study. Before this current iteration I manually logged over 3,000 upsets and what I found is that most of my upsets were self-induced. I’d be in a calm environment, but then become upset about something. I wanted to use technology because I was afraid of bias and I know I was missing some upsets.
How Did He Do It?
I used the HeartMath EMWave2 that measures heart rate variability and indicates when you’re in and out of coherence. When I was out of coherence I captured that as an upset. I would stop what I was doing and use an audio recorder to keep track of the time, how long I was upset, the reason, and what method I used to recover. I tracked 71 sessions (each session was 25-45 minutes) totaling 42 hours of tracking time. I logged 1292 upsets during this period.
What Did He Learn?
Paul analyzed his data and found some very interesting insights about his upsets, his reasons for being upset, and the effectiveness of his recovery techniques.
I found that I was triggering an upset every 2 minutes. My wife said something must be wrong with me, but this stayed relatively constant through the tracking period. I started to think of it like skiing a mogul course. The moguls didn’t move, it was about how effective I could move through them. And, dealing with upsets is like playing whack-a-mole. They come fast and furious and every second counts.
For recovery I was able to find that my most effective technique was breathing. By returning to six breaths per minute routine I was able to improve recovery time from 33 seconds to 17.8 seconds. It was the primary way I could remove myself from being upset and make myself calmer.
We want to thank Paul for presenting this great QS project at the Bay Area QS Meetup group. Make sure to watch the full talk below to learn more about Paul’s methods and findings, then hop over to his website where you can read about how he tracked his stress during this talk.
Lee Rogers has been collecting data about himself for over three years. The daily checkins, movements, and other activities of his life are capture by automatic and passive systems and tools. What makes Lee a bit different than most is that he’s set up a personal automation system to collect and make sense of all that data. A big part of that system is creating an annual report every year that focuses on his goals and different methods to display and visualize the vast amount of information he’s collecting. In this talk, presented at the Bay Area QS meetup group, Lee explains his data collection and why he values these annual snapshots of his life.
Philip Thomas is a software engineer at OpenDNS. He’s been collecting a lot of personal data since college, first starting with his custom built beer tracking system. He then moved on to slightly more sophisticated personal data. As the data started to pile up in services and systems he started to explore what it would take to create his own custom personal dashboard. In this talk, presented at the Bay Area QS meetup group, Philip explains how he built his dashboard and why it’s so valuable to him as he tracks his life.
On March 26th we hosted a fantastic Quantified Self Bay Area meetup at the new Exploratorium space overlooking the San Francisco bay. Over 180 people came together to mingle, learn about new self-tracking tools, and hear from our wonderful speakers.
We were lucky to have four great presenters talk about their personal self-tracking process. Philip Thomas spoke about building his personal dashboard. Maria Benet talked about how she used self-tracking to lose 50 pounds and take up sport she never dreamed of. Michael Cohn described his use of time tracking and personal commitment contracts. Lastly, Sky Christopherson gave us an update to his wonderful self-tracking talk from a few years ago and how that turned into helping the Women’s US Olympic Track Cycling Team bring home a silver at the London Olympics in 2012. Videos of these talks will be up soon!
When you move from a small town to a big city you’re faced with a number of interesting challenges. How do you get around? Should you sell your car? When Valerie Aurora moved to San Francisco she faced these common roadblocks, but she also encountered something new: being harassed. In this great talk, filmed at the Bay Area QS Meetup, Valerie explains her rationale for tracking street harassment incidents and what she learned about herself and her new city in the process.
Sara Cambridge is an interaction designer and a frequent contributor to the Quantified Self community. This past spring she was tasked with creating a unique information visualization as part of her graduate coursework at the UC Berkeley iSchool. Given her interest in QS she chose to use her experience with tracking her diet using the Eatery mobile app as the basis for her visualization project. Using the Eatery led her down an interesting path that helped her understand her own eating habits, how she compares to others, and how people “really” rate other’s dietary choice. (Filmed at the Bay Area QS Meetup)
Evan Savage has panic attacks, especially triggered by caffeine while driving. In late 2011, he was having multiple panic attacks a week. He didn’t want to take drugs, so he made his own recovery plan – logging his food, exercise, and panic attacks. He eliminated caffeine, and thought he had recovered, then relapsed. In the video below, Evan tells the courageous and entertaining story of how he has navigated through recovery and relapse multiple times, and what he has learned about how to thrive. (Filmed by the Bay Area QS Show&Tell meetup group.)
Mike Winter does a lot of crazy research projects, including building an autonomous motorcycle. But when his daughter was in a bicycle accident a couple of years ago, he started thinking about bike safety. Specifically, he built a device with an Arduino CPU and a few sensors that attaches to your bike and connects with your smartphone. Mike’s invention will let bikes and cars be more aware of each others’ presence, track close calls, and alert the cyclist to any upcoming hazards. In this entertaining video below, Mike shows off the device as well as a pair of his own home-brewed Google goggles. (Filmed by the Bay Area QS Show&Tell meetup group.)
Jeremy Howard has been studying Chinese for the last two years. The method he uses is called spaced repetitive learning, found in SuperMemo and Anki, in which you prompt yourself to remember something just before you’re about to forget it. Jeremy wrote his own software to track his learning, including variables such as time of day, what he ate, when he slept, what activity he was doing, etc, and correlated it with his learning. In the video below, he shows some of his data and talks about what surprised him along the way. (Filmed by the Bay Area QS Show&Tell meetup group.)