There are numerous studies that demonstrate the benefits of periodic, short-duration fasting, such as weight loss, improved insulin sensitivity and brain function, immune system regeneration, and longevity. I’ve been a fan (and practitioner) of intermittent fasting for several years, but other than an occasional 24-hour liver cleanse or protein fast, I had never done any extended fasting. My original plan was to do a “traditional” water fast, where nothing but water is consumed for a period of 3-5 days. However, during my research I began looking for ways to get all of the benefits of a water-only fast, but in a way that was “easier” (both mentally and physically), safer, and would minimize catabolic effects (loss of muscle mass). Enter the “fasting mimicking diet”… [Read more…]
(Note: This experiment was inspired by a Reddit user who recently posted a graph showing their heart rate while watching the movie Interstellar).
Last week I went to see Interstellar (in IMAX, for full sensory effect!) and captured some biometric data to see how I reacted during the course of this nearly 3-hour movie. I wore a Polar H7 heart rate monitor paired with the SweetBeat HRV app on my iPhone, along with my wrist-worn Basis B1. I exported the raw data from SweetBeat using their built-in export tool, and my Basis data using my Basis data export script.
Whereas the original experimenter only tracked heart rate, I wanted to analyze:
- Heart Rate
- Heart Rate Variability (HRV)
- Galvanic Skin Response (GSR)
Interestingly, my heart rate trend (on the left, below) looks very similar to the original Reddit user (on the right)! Both of us are using data from our wrist-worn Basis devices – in my case, the older B1 model, and for the Reddit user the newer Basis Peak. Although the Peak is capable of capturing more samples, the data returned from Basis is always an average value for each minute.
However, SweetBeatLife is recording data at a resolution of 1 sample per second via the Polar H7. The per-second pulse data is a little bit jumpy and hard to follow (in gray), so I’ll also include a 60-second moving average as well (in blue):
It looks very similar to the data recorded by my Basis. Good!
Heart Rate Variability (HRV)
Heart Rate Variability uses a technique in which the spaces between heart beats are measured, and is a good way to measure stress via an individual’s “flight or fight” response (the higher one’s HRV, the better). There are a number of ways HRV can be calculated, and in this case we are using what’s known as rMSSD (root mean square of successive differences). You can check out Wikipedia for a pretty good overview of HRV.
Galvanic Skin Response (GSR)
Galvanic skin response (also known as skin conductance) can be used as an indication of psychological or physiological arousal:
My GSR started out rather elevated, which I guess was due to a combination of anticipation for the movie to begin as well as my eyes getting adjusted to the huge IMAX screen (and my body adjusting to the temperature in the theater). I was clearly into whatever was happening on-screen between 1:50 and 2:20!
Putting It All Together…
Now, if we look at all of the visualizations together, we can easily spot key moments in the movie (no spoiler alerts here, but if you’ve seen the movie you should be able to figure out what was happening in each area!), or when I might be internalizing some deep analysis of gravity and multidimensional spacetime, or simply bored (the movie takes some time to really get going!). We can also see when my stress response kicks in or relaxes (phew!).
Looking back at the data, you’ll see there is often an inverse relationship between heart rate and HRV, which makes sense – if your heart starts beating faster, you are most likely encountering more stress, which increases your sympathetic response and thus lowers HRV. Galvanic skin response typically is reflective of one’s sympathetic autonomic nervous system response (will increase as HRV decreases).
I think a great experiment idea would be for a bunch of self-quantifiers to all go see the same movie so we can all share and compare our data! Shoot me an email if you’d like to get involved.
The first question I usually get from people is, “so, what are you tracking?”, so I have compiled a list of experiments I am currently conducting (as well as planning to), which I will update regularly. For me, “tracking” is simply the collection of data – the real fun is constructing experiments around that data to identify correlations or test theories.
One challenge is that I can only conduct a few experiments at any given time – otherwise, actions related to one experiment can interfere with biomarkers that may need to be tracked in another experiment (especially when trying to establish baselines). Another is that some experiments can take a really long time to conduct, especially when trying to establish baseline numbers (see previous point) or waiting for test results (i.e., telomere testing currently takes around 8 weeks to get results). This also explains why I haven’t been posting as frequently as I would like!
I’ve set up a page where you can check out my in-progress and planned experiments. I will continue to update this list, and as I complete my n=1 experiments, I will link them to their corresponding write-ups. Don’t hesitate to reach out (you can email me at bob [ at ] quantifiedbob [ dot ] com or @QuantifiedBob on Twitter) if you’d like more info or if you working on similar experiments!
In Progress (view details):
- Telomere Analysis
- Bulletproof Diet – Cholesterol/Bloodwork
- Central Nervous System (CNS) Training
- Stress Management with Heart Rate Variability (HRV) Training
- Skin/Scar Repair
- Quantifying the Value of My Time (Time Optimization)
Planned (view details):
- Cognitive Improvement using Dual N-Back Training
- Oxaloacetate and Glucose Tolerance (Anti-Aging) Effects
- Environmental Monitoring
Yesterday, as I do each year, I dusted off my seersucker suit and attended the Belmont Stakes, the final leg of horse racing’s Triple Crown. While having my Sunday morning Bulletproof Coffee and exporting data off my Basis B1, I realized I had unintentionally captured a data points that could quantify my day of gambling at the track! I have been meaning to conduct some experiments around quantifying “thrill”, so I threw the following chart together:
(click image to enlarge)
I didn’t set out to structure this as an experiment, so unfortunately I had limited data to work with and this is all more observational and to be taken with a grain of (Himalayan pink) salt (but still fun!). I threw out most of the data points collected by my Basis B1 (steps, calories, skin temp, air temp) as they didn’t appear to correlate with anything or change significantly. Most research shows that galvanic skin response (GSR), heart rate, and heart rate variability (HRV) give the best indication of excitement/thrill/arousal, so I plotted heart rate and GSR.
- Heart rate elevates to maximum levels in 3, sometimes 4 instances – at time of placing bets, right at the start of the race, and after the race is over and I won money (interestingly, hear rate tends to decrease while the race is happening). There is also a spike when I go to cash out my winnings
- Losing does not result in any post-race heart rate spike
- Galvanic skin response increases as the race is happening (excitement and arousal?), usually starting from a baseline and peaking at the finish (especially if I stood to win big!)
Issues, and what I would have done differently:
- I am only able to obtain 1-minute average readings off of my Basis B1. Ideally I would like to have 1 reading per second, especially during races, which typically last no more than 2 minutes start to finish
- I would have properly synchronized my time readings with the “official” clock at Belmont (my timestamps appear to be about 2 minutes off the “official” race start times, so I shifted my data accordingly)
- I would have worn a chest strap to better monitor heart rate (the optical bloodflow sensor on my Basis was really flaky, and had significant dropouts)
- This would have also allowed me to capture HRV, which would have been ideal
- I didn’t track the times I was researching/placing my bets, but looking at the charts it seems like it resulted in elevated heart rate
- I had a few drinks throughout the day (3 to be exact, spread over the day) so not sure if/how that had any impact
This has piqued my interest in thinking of ways to better construct experiments to quantify thrill/arousal, especially as it relates to gambling. To be continued!