Tag Archives: HRV
We hope you enjoy this week’s list!
The Global Open Data Index by The Open Knowledge Foundation. This isn’t an article, but rather an really nice portal to explore open data sets from around the world.
Eight things we learned about HealthKit from Duke, Oschner by Jonah Comstock. An interesting piece here detailing how two large healthcare systems are using Apple’s Healthkit.
Connected Health: Improving Patients’ Engagement and Activation for Cancer-Related Health Outcomes by the President’s Cancer Panel. Very short publication here that outlines how the President’s Cancer Panel is thinking about new changes in the health system and health technology.
Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images by Anh Nguyen, Jason Yosinksi, and Jeff Clune. This in not a typical entry into our weekly What We’re Reading as it doesn’t appear to be directly related to self-tracking or Quantified Self. However, I found it fascinating and a great reminder that algorithms are not infallible.
Visualizing HR, HRV, and GSR While Watching ‘Interstellar’ by Bob Troia. Inspired by a Reddit user who tracked his HR while viewing Interstellar, Bob Troia set out explore his full physiological response by tracking heart rate, heart rate variability, and galvanic skin response. Some great data in here!
Stress Snail by Pavel Zakharov. Pavel uploaded this unique visualization to our QS Forum earlier this week. This visualization represents his heart rate, activity, and stress during a particularly stressful day when he was completing a driving test. If you have ideas or thoughts on the visualization make sure to share them in our forum!
This Week on QuantifiedSelf.com
Greg Schwartz: Quantified Dating
David Joerg: Building My Personal Operating System
Join us at our upcoming QS15 Global Conference and Exposition on June 18-20 in San Francisco to learn how heart rate variability can indicate how relaxed or stressed you feel when meeting with other people.
We’re pleased to have a self described heart rate variability hacker and veteran QS’er Paul LaFontaine share how he uses heart rate variability readings to improve his effectiveness when engaging in discussion with others. Paul used off the shelf technology including a Polar Heart Rate Belt and a Heart Rate Variability Logger app to record his heart rhythms during different stressful and relaxing activities. Once he had these baseline readings, he compared them to hundreds of hours of meetings to find patterns in the data and to pinpoint what was associated with relaxed, productive discussions or stressful, less productive interactions. Some of the source of stress may surprise you!
Paul’s Heart Rate Variability session is just one of the many hands-on, up-to-date, expertly moderated sessions we’re planning for the QS15 Global Conference and Exposition. This year, QS15 is going to be two full days of self-tracking talks, demos, and in depth discussion, followed by a third day for a grand public exposition of the latest self-tracking tools. Join us at the Fort Mason Center on the San Francisco Waterfront. We’ve made some early bird tickets available for readers of the Quantified Self blog (for a limited time): Register here!
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.
In this video from the always great Meetup of the London Quantified Self group, Gary Monk describes his detailed relaxation and focus experiments using continuous HRV measurement with HeartMath’s Inner Balance sensor in the course of his normal daily life.
Last week we brought you a look into some of the interesting Quantified Self tools that were debuted at CES. Here are a few more we noticed from the deluge of CES coverage. Thanks to MobiHealthNews, Gizmodo, Engadget and many QS friends for the tips.
Withings Smart Body Analyzer (WS-50)
The latest wireless scale from Withings adds some interesting new sensors: resting heart rate, ambient air quality (CO2) and room temperature. The combination of physiological and environmental monitoring, while simple in this case, opens many new possibilities for Quantified Self projects.
Measures: Weight, BMI, Fat Mass, Heart Rate, Room Temperature, Room CO2
The Zensorium Tinke is a small sensor and companion app for iOS devices dedicated to helping users understand their health and wellness. This is a really interesting variation on the emerging theme of Heart Rate and Heart Rate Variability self-monitoring. The Tinke has no battery and no screen. Instead, the small optical sensor plugs directly into the iPhone.
Measures: Heart Rate, Heart Rate Variability, Blood Oxygen, Respiratory Rate
A similar approach is used by the Masimo iSpO2, where the focus is on blood oxygenation.
Measures: Blood Oxygenation, Heart Rate, Perfusion Index
The Mio Alpha boasts of continuous and strapless heart rate measurement. Using technology developed by Phillips, the Alpha uses optical heart rate sensing at the wrist and a soon to be released mobile app. What once seemed like difficult technical magic is on the verge of becoming commonplace.
The Mio Measures: Heart Rate
Sync: Bluetooth 4.0