Category Archives: Quantified Self

Ending Two Years of Quantifying Myself

My first blog post on self-quantification was April 6th, 2014. I went pretty hard at it for the last two years spending a fair bit of money and doing experiments of various kinds to see how my body would react. My favorite was taking heart rate variability readings while having a tooth drilled at the dentist. After a fair number of insights, I’m ending two years of quantifying myself.

 

Ending Two Years of Quantifying Myself

It is not really a full retirement as I will continue to monitor things as I did before this two year period. As a runner and triathlete, I was monitoring my heart rate many years before entering the QS scene. So monitoring various mood states and body reactions like heart rate variability will continue. I get a lot from it.

What I am retiring is the identity of “scientific publisher of N=1 studies” and being a “quantified-self guy.” As part of this identity I was regularly publishing this blog, tweeting, leading a QS Meetup and attending the big QS conferences. There was a specific discipline around that and I’m going to let that go.

The overall lessons I learned after these two years:

  • You can learn anything you want with the internet resources available. I started as a guy curious about stress readings and got pretty conversant with heart rate variability to the point of being a junior partner in presentations with friends who were PhD’s on the subject.
  • The summary finding on all my outcomes is if we human beings get a good nights sleep, drink plenty of water, eat a modest amount of calories, exercise with regularity and hang out with other people we like, we feel pretty good most of the time. My grandmother told me that years ago but I had to use  science to validate it.
  • A lot of Quantified Self is Quantified Storytelling. At QS EU #15 Doctor James Heathers coined this phrase as he pointed out that the controls are the problem. In a noisy environment achieving any level of control is extremely difficult. And doing the math with any sense of sufficient data can absorb your time for extended periods. With a lot of noise and smaller data sets, we have to push our story a bit more as not having a result is not very compelling, particularly if you are presenting to groups by blog or presentation.
  • The only negative finding I had is that I suspect the entire supplements industry is a massive exercise in commercial placebo. I did not get any meaningful results from any of the supplements I tried that were not overshadowed by sleep, water, and food (see bullet #2).
  • The body is incredibly resilient. Our story that one night out indulging will ruin our health is just wrong. I had several physically stressful periods result in heart rate variability and blood pressure readings that were virtually unchanged from non-stressful periods. The underlying physical system is very stable and completely separate from, our beliefs about it.
  • People want to read about brands and ultimately Google drives traffic to a blog, people don’t seek you out based on the quality of content. The two biggest drivers to this blog were when I indexed posts in Google that talked about Apple Watch and another service that was getting good press. Both drove big spikes in traffic and in my opinion were halfway to product reviews. That Apple Watch mention still drives traffic. It is just the facts on being a publishing type. The people want to read the reviews that helps them buy stuff.
  • Our stories and beliefs about our condition are the entirety of our experience of our condition and thus, are our condition. Quantified Self is a place of stories and beliefs with data to enrich them. Studies have to  be conceived, data gathered and the results analyzed. And if we declare success in altering heart rate variability through head position then we must have the story that a changed heart rate variability is desirable. When you get to that level, it is an arbitrary definition of what is good.  Most of my QS work lived under an umbrella of some form of story. The story is the thing.

I remain a supporter of Quantified Self and its unique place in a history of technical change and its contribution to the continued dynamic way we use technology to shape our behavior. QS as a separate and unique group was big when it was kind of hard to get the data together and you had to rig your own sensors. Now we all are starting to live with easy data capture and quantification. The QS community becomes all of us.

The study I did on my To Do List was one that really altered my perspective. When I let my to-do list go and watched what things I started doing naturally from a place of interest, QS matters were not part of the mix. My interests had moved on, and doing things from a place of fascination and interest is the story I want to write. And the story is the thing.

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Part 2: Takeaways from pre-workout caffeine’s effects on performance

Post by: Tim Hanrahan

About 6 weeks ago, I came to a realization. I had been trying to drink coffee 30 minutes before a workout based on some hearsay and research to confirm its positive effect… but I had never been tracking my pre-workout caffeine’s effects on performance. I thought I was feeling good, but sometimes I didn’t really feel any change. How can I know for sure? And because I do different forms of workouts at different times of the day, what’s the best combination of variables for the highest boost?

That’s what I was intrigued to find out and I tracked and reported my initial takeaways at the end of August. The summary: I found that drinking coffee 30 minutes before a workout does in fact give me a boost, but it varied between how much of a boost it gave me. Going forward into September, I wanted to hone these results in even more and test a few more variables.

Below is a breakdown of my process, results, and new takeaways.

 

Process:

I again used Apple Health to track the quantity and frequency of caffeine consumption. By the end of my last tracking period in August, I had become a 3-cup a day coffee drinker, primarily using my trusty Kuerig and K-cups that contained 150mg of caffeine.

I also used QXL’s own DIY Tracker to gauge my feelings after a workout and analyze my performance. I was extremely disciplined to record my results and in general reflect about my fitness. I was of course hoping for that “Very High Boost” and the results began to show a pattern after another month tracking my progress.

pre-workout caffeine's effects on performance
My custom survey to rate how big a boost the caffeine had on my workout, using the QXL DIY Tracker.

 

Results:

As part of my initial tracking, I made sure to note when I was having coffee before working or with breakfast in the morning. It was good background information to have, but after 4 weeks, I began to understand my daily routine and didn’t feel the need track these instances. This decluttered my data to only show the times of my workout routines and my boost rating from there, noting on the side the days I had 2 or 3 cups of coffee.

Having said that, here’s a look at my data of my reflections on the caffeine’s effects, illustrated through the DIY Tracker’s automatic recordings to a Google Doc.

pre-workout caffeine's effects on performance
An overview of my September data, focusing more on just the caffeine intake before a workout.

 

Takeaways:

I believe I have found my sweet spot.

When only focusing on my desired “Very High Boosts”, the common element was that it came after a 3rd coffee, before I played basketball at night around 8pm. During these instances, I felt a noticable change multiple times. I was playing with a sharp attention span and ability to make quick decisions, essential for being a point guard. I play recreationally in competitive leagues and had some of my best games in the past 2 months with these pre-workout variables lined up. In fact, drinking a 3rd cup of coffee 30 minutes before playing basketball led to an 89% chance of getting the optimal “Very High” boost.

To also arrive at this conclusion, I compared my “3rd cup of coffee” variable to my performance playing at the same time (8pm) but having only 2 cups of coffees during the day (1 of which, 30 minutes before). I also included my performance after doing a Pilates workout, which was almost always after my 2nd cup of coffee during the day. I noticed there was a high propensity for a boost, whether slight or solid 79% of the time, but only the optimal “Very High” boost 14% of the time.

Conversely, I compared the boosts to a few morning pilates workouts I did during this time period too. I failed to really feel more than a slight boost, providing the first piece of evidence to me that I’m just not a morning person (as my routine also dictates now). This inspires me now to research… What is the cummulative effect of caffeine throughout the day as more and more is consumed?

Finally, I was also able to quickly answer one of my other questions from back in August. I wanted to test the variable of consuming more caffeine than usual during the 30 minute pre-workout period and see how that would affect my performance. I already felt comfortable with my K-cup amount, but I had to see if even more would be even better.

pre-workout caffeine's effects on performance
I tried a large Dunkin Donuts coffee (20 fl. oz, 244mg caffeine) because I had to play in a tournament in the morning. I felt the jitters and it affected my game. Too much caffeine?

Au contraire. It actually made my performance worse. The added caffeine made me too antsy and anxious. I actually was conscious of quick, edgy, and fidgety movements that translated poorly on the court. I played like I was trying to do much and go too fast instead of letting the game come to me. In basketball, just like in consuming caffeine, or life in general, it’s all about finding that balance. I’m glad it only took me a couple of different gamedays (and losses) to keep my caffeine intake in moderation. Sometimes it means going too far the other way to better hone in the optimal place along the spectrum.

It took 6 weeks, and some untracked experiences before that, to A.) confirm my research and hypothesis that caffeine 30 minutes before a workout positively impacts my performance, and B.) find the right balance of how much caffeine both at the time and throughout the day yields my optimal boost for best performance. It’s a gratifying point in my journey: to understand myself even more to gain a better chance to achieve my goals on the court. That’s what QS is all about and that’s what you can do too. Everyone’s different, so you can create the DIY Tracker to help you follow whatever passion you want to pursue too.

pre-workout caffeine's effects on performance
This was me, but playing basketball. This could be YOU: rock climbing or _____________.

Keeping Motivated With Tricks While Quantifying

I was looking at the various things I am tracking and thought about those tests I have failed to complete. And others where I consistently collected data despite the measuring being pretty complex and tedious. Why did my motivation on some projects evaporate and in others it remained strong? How was I keeping motivated?

KeepGoing

For me doing Quantified Self tracking of one topic has a similar psychological feel to running a long distance. I have to use similar mental techniques to tricking myself into enduring when faced with plodding along for another mile or taking my 30th heart rate variability reading while zapping my brain with electricity.

One that died on the launch pad. Only one reading then ignored.
One that died on the launch pad. Only one reading – then nothing.

When I run I break the challenge into smaller buckets. I pick a point in the distance, say “I know I can run to that” and I plod on until I get there. Then I do it again. I completely understand that I am tricking myself and that the total run distance is much longer, but there is something that works for me when I do it. I pulled through a marathon with pretty tough leg cramps starting at mile 18 doing that.

My QS the tricks are similarly simple. I have found the most effective is setting an alarm on my Pebble watch when it is time to take a reading. Not my phone, very specifically the Pebble. There is something that is less obtrusive about it for me so I accept it. And it breaks my stride so I can turn my attention to the reading. With the phone, I tend to get irritated by the notification, dismiss the alarm and return to what I was doing without taking the reading.

If you want to look at something with any precision you will need at least 30 data points. And if you measure once a day then the math is easy, that will be a month of disciplined, repeated readings. If you want 100 data points so you statistical outcome is stronger you are talking about three and a half months. That is a long time to control the circumstances of the reading and measure with consistency day after day.

BigReadings
And one that launched well. Multiple metrics a day consistently done.

Many tool providers try to automate the problem away. The theory goes that automated data gathering removes the motivation problem. But it is not that simple. If I get on a Withings scale once a day for 30 days the data is easily captured. But to really test what impacts my weight I also have to vary my eating, or my exercise, with absolute consistency to precisely track my potential outcomes. And that consistency takes motivation too.

There are some beginning efforts to try and help. One I like is Whatify. The service notifies you with text reminders on which randomized action to take and they do the math after the study is done. You just come up with the study. The only drawback is you cannot see that point when the study will end. It is like going for a run and the only feedback you get on your progress is a voice saying “keep going” or “stop now.” Without knowing the end point and seeing my progress I have a hard time keeping motivated.

As you look at building out approaches to things you want to track and test, ensure you are keeping motivated by finding the small tricks that will keep you collecting data and varying inputs effectively. How you are inspired to do something consistently is unique to you. Once you understand that you will reach the finish line with good data and great results.

 

 

Gwern’s Excellent Review And QSEU15

This week I was in Amsterdam at the European Quantified Self conference and it was an inspiring event. I have huge appreciation for Gary, Ernesto, Steven, Marcia and Kate for putting on a fantastic program. I always come away from theses events inspired to up my QS game.

My Show & Tell on HRV While Transition To Ketosis
My Show & Tell on HRV While Transitioning To Ketosis

Even before the conference kicked off, my post last week on the poor results from Bitter Melon really got everyone’s collective juices flowing. Some great comments and suggestions, with Gwern Branwen going above and beyond by reviewing my data and taking it through advanced mathematics using R. His work is awesome and I plan to conduct a full followup.

At the conference I had a chance to collaborate with Marco Altini in presenting both a breakout and a how-to session. I have been a fan of Marco’s apps for a long time and got a chance to meet him in person last year. This chance to collaborate was a real pleasure and I think the sessions went well.

I also met Dr. James Heathers (here he is on the Ben Greenfield podcast), an Australian skull ring wearing rock and roll scientist. He gave a great talk on the science of Heart Rate Variability (HRV) that included tips like voiding your bladder before taking a reading and how drinking water can significantly increase your HRV. I also had the pleasure of joining him for dinner and enjoyed a broad-ranging discussion that included his stories of research, observations on Quantified Self and a thorough evisceration of Sam Harris.  Good time.

At the conference itself there were thirty-seven talks and a much-improved conference format allowed me to catch them all. Wearables and the obsession with what technology can do for us seemed much muted in comparison with last year’s conference.

In the “all is connected” category, two presentations stood out for me. Justin Timmer gave a fascinating view of his tracking of 40 different variables over the course of one year. The big takeaway was that all his variables were connected and that each seemed to influence every other. Ahnjili Zhuparris gave a view on six months of her shopping, Facebook language use, & music listening behaviors during different phases of her menstrual cycle. A fascinating look at how much our underlying systems connect and effect the whole of us.

In the “surprising outcomes” category Robby MacDonnel presented data on how distracted he was while driving. Despite having judgments about the distracted driving of others, he found himself on his phone while driving over 20% of the time. It was a great talk. Rocio Chongtay was able to show how different music changed outcomes for her in as diverse a set of activities as programming and accuracy while firing a bow and arrow.

A useful session for me was on reading speed and neuro-technology. Kyrill Potapov’s talk titled “Finding My Optimum Reading Speed” outlined the use of Spritz reading technology and how with the help of his students he was able to test increases in reading speed without a reduction in comprehension. Definitely a technology I am going to play with.

A breakout session on neuro-technology had a lot of skepticism in it regarding any of the existing technologies, and TDCS was particularly viewed with some hesitation. I’ve started a TDCS experiment though I am rethinking it now. There were some strong opinions on binaural beats and I’ll withhold what I heard until I publish my A/B test on the effectiveness of Brain.fm’s meditation beat on my Muse calm scores.

So it was with Gwern’s Excellent Review and QSEU15. An action packed quantified self week.

 

 

Superpower Series: Variability Basic Training

Before you begin taking readings in work sessions and meetings you have to become familiar with the pattern and connection between your circumstances, Heart Rate Variability (HRV), and breath. Your breath rate signals to your nervous system whether your circumstance calls for an accelerated state, or a relaxed nervous state. Conducting repeated sessions will allow you to see the relationship.

Exercise: Using basic kit take a measurement each morning for five minutes. While doing so, breathe six times a minute. That means breath in five seconds and out for five seconds. You can start with a smaller period if you are uncomfortable  and need to practice. Even at smaller intervals make the breaths even and consistent. Afterward look at the intervals between heart beats to see how well your breath and HRV relate to each other.

If you are relaxed the measure of RR intervals will go up and down evenly with your breath. This means your Parasympathetic Nervous System (PNS) is applying the brake to put you in rest and digest state. Here is a graph of my RR intervals during a five minute session in a completely relaxed state:

Slide1

I have had many sessions where despite regular breathing I could not enter a relaxed state. Here is a session where I was thoughtful about a variety of to do’s while trying to bring myself to a relaxed state. These Upsets were evident in the graph of my RR intervals:
Slide2

You can see in the intervals have periods where there is not much variability. My thought process was accelerating my Sympathetic Nervous System even though I was sitting quietly breathing in a regular rhythm. In another session I was generally relaxed and in the zone then had a thought that interrupted my flow. I let the through go and returned to breathing and recaptured my variability. You can see the interruption and return in the red circle.

Slide3

In another session on two occasions I had Upsets in the flow of the session and was able to recover twice. You can see these episodes in the red circles in this chart.

Slide4

The exercise of breathing regularly and taking your HRV measurement for five minutes a day will give you a baseline for when your system is Upset by different thoughts, and when it is responding to your breath while relaxed.

If you want to learn more about developing a Superpower read about Giving a Speech.

Superpower Series: Why You Should Memorize Your Speeches

One superpower that some people seem to have mastered is the ability to stand in front of a group of people and give a speech. For most people it is the most stressful of events, up there with losing a job and divorce. So how can you use Heart Rate Variability (HRV) to keep your fight or flight mode from kicking in and you entering a panic state in front of the group?

Well, it does not appear you can avoid the fight or flight response standing in front of a group of people. From measurements I have taken when speaking I think that the only strategy you can employ is to have more material embedded in memory so you just speak automatically without having the engage your prefontal cortex.

The mechanics of this are straightforward. When you are in fight/flight your body optimizes blood flow to get you out of danger. Blood flows to your limbs and the back of your brain, allowing you to maximize your ability to react. When you are in this reaction mode your thinking brain is offline. You can’t wing it when your thinking brain is offline.

I took readings while speaking at two different Quantified Self meetups. This is a very sympathetic crowd. There is no pressure to perform for this crown. And I have experience speaking publicly, from corporate engagements to speaking competitions for Toastmasters. I enjoy public speaking, so I should be on the more relaxed end of the spectrum. The data shows that even experienced speakers are not immune to the stress of presenting to groups.

As a baseline for compare readings from a meeting with senior people that I am working for as I presented in an earlier post. This was a high intensity meeting where I was expected to present information. The graph shows with blue bars where I experienced the fight/flight impulse.


Slide4
Readings on a speech I did at the meetup July 28th of 2014 showed how much stress the system kicks in when on a stage. I started the measurement about five minutes before the speech and did some breathing exercises to see if that would have an effect on my measurements. Here is me giving the speech.

Qs Speech

The breathing exercises did help kick in my relaxation response for the first five minutes of the reading. Once I got to the podium, however, the fight/flight kicked in. I spoke for 14 minutes and answered questions for ten minutes. You can see the readings in this graph: The red box shows the period in which the speaking portion of the presentation took place.

Slide1

A second speech showed a similar pattern. In March of 2015 I spoke again at a Quantified Self meetup to a smaller group. Again a very sympathetic group. I knew the material and was pleased to be presenting. This was a shorter speech, five minutes speaking and five minutes of Q&A. You can see from the chart and the red box that the during speaking portion I was almost entirely in fight/flight state.

Slide2

Why this is important is  as described above the pre-frontal cortex is offline when in this state. Meaning that you can’t think through what you are going to say in real time when you are on the podium. You are in reaction mode. So rehearse the material. When a slide comes up, you react to what you have memorized. I have had experience of “watching” myself giving a speech when I have memorized the material and am bouncing along well. And I have had the experience of freezing in place when I had nothing in my deep memory to react to. And I just stared blankly at the audience.

So memorize your material before you get up to speak. Your physiology will ensure your brain is offline. If you react well throughout the speech you will give a great speech. Even this guy had to memorize his speech:

Braveheart

Parasympathetic Flatline Talking versus Listening

I wanted to look at how often I entered the Parasympathetic Flatline while in a 1:1 conversation with a colleague by phone. For the discussion I read by heart beat intervals using a Polar H7 heart rate belt and the Heart Rate Variability Logger app for iOS. I also recorded my side of the meeting on a smart phone. When the meeting was complete I downloaded my heart beat intervals via csv file and pulled them into excel. Once in excel I used a formula mechanism I created that graphs segments where more than 10 consecutive interbeat intervals are less than 17 milliseconds apart.

During the 60 minutes session I measured 4,451 heart beats and the intervals between them. Of those intervals, 14% were in groups of consecutive intervals that were close together, meaning during 14% of the meeting I was in what I call Parasympathetic Flatline. This measured the periods where I was in fight/flight mode during the discussion.

Here is a vizualization of the meeting:

Slide1

In the session the forty-seven stress events triggered. Of these, 22 of 47 occurred when I was talking and presenting information to my colleague. 25, or 53%, occurred when I was listening to my colleague.  When listening to the recording, it is clear that the stress event, even when occurring when I am talking, begin when I was no agreeing with my colleagues response or trying to move him to a different position. The stress response was a result of not liking the direction the conversation was going.

Again physiology has shown that anticipating and trying to shape another person’t response is the source of stress in a 1:1 interaction. I once thought presenting my own opinion was a source of stress but that has turned out not to be the case. The stress, it appears, is not agreeing with someone else presenting their opinion.

Added clarification: From Twitter, fellow QS’er Gustavo (@GGlusman) asked the percentage of time I was talking versus not. Pushed by the question I went back beat by beat and looked at the session. As I reported above 736 beats were “in stress ” meaning that those beats were in a grouping with more than ten beats that occurred with a difference in beat interval less in 17 milliseconds to the adjacent beat. Of those beats in stress, I found that 238 were while I was talking and the remainder while listening. So that means 38.5% of the stress beats occurred while I was talking, 61.5% while I was listening. Impatience while listening was clearly more stress creating than flapping my gums. Thanks to Gustavo for asking the clarifying question!

Using the Parasympathetic Flatline

Using the Parasympathetic Flatline I analyzed a discussion with a colleague. I was following up on a topic that was not controversial. We had discussed this topic about a month prior. The colleague and I get along in a positive way.  So this should have been a relatively stress free and short meeting.

I used Marco Altini’s Heart Rate Variability Logger and a Polar H7 heart rate monitor to gather the base data while recording the meeting with my smart phone. Pulling that data into a spreadsheet I used my Parasympathetic Flatline model to determine at what point in the meeting I was experiencing physiological stress. I pulled the recording, the heart rate variability readings and the transcript into a timeline graph.

Slide1

What we see here is when I talked (green), when my colleague talked (blue) and when I was experiencing a physiological event of what I call Parasympathetic Flatline (red), or stress. There are specific points in the discussion when I was amped up, but they were not what I expected.

I had a hypothesis that I was entering these states when I was putting myself “out there,” however I had one moment about 3/4 of the way through the meeting where I really pushed the boundary of a sensitive topic but I did not experience stress. I was synched with my colleague and the discussion did not trigger stress at that point.

There were four points in the discussion, however, that I entered a heightened state when I wanted the conversation to go in a different direction. My agenda was not being followed. In the first two, early in the conversation, I wanted to hear the answer to the question more directly. I was impatient. In the second two, I had the information I needed and wanted to wrap up.

It appears that difficult topics are not stress inducing when discussing them with a colleague when we are in synch, but my overall judgements about the progress of the discussion seem to trigger an aroused state. It is our judgements about the situation that may be the source of stress.

Testing the Parasympathetic Flatline

Last week I proposed measuring a Parasympathetic Flatline (PS Flatline) where at least ten successive heart beat intervals were close together. This differs from using 30 second averages for rMSSD, a time based measure of average intervals. I wanted to to a side by side comparison to see which of these methods more accurately could point me to moments when I triggered a shutdown of my Parasympathetic Nervous System which allowed the fight or flight reaction to run things.

I measured several meetings where I was able to audio record the proceedings while measuring my heart rate. I used my Android phone to record the audio, a Polar H7 heart rate belt to pick up my heart rate and Marco Altini’s Heart Rate Variability Logger to capture the data. Afterward, I downloaded the csv files for both the rr intervals and the 30 second rMSSD.

The meeting was 55 minutes long and included one person in the room with me and one person on the phone. We were discussing a topic I was comfortable with and an activity I had experience doing. I was briefing my colleagues on a time schedule and details. I was in a relaxed state going into the meeting and did a short two minute breathing reset using BreatheSync prior to the meeting.

In previous studies I had determined that a 30 second rMSSD under 48 was probably a stress state. I had used several stress events to create this baseline. When looking at this meeting, however, I was disappointed to see that using this method definitely overstated the number of stress states. The graph below shows blue bars where I had a 30 second rMSSD under 48 and you can see it shows I was in that state for much of the meeting.

Slide1

This was not my experience of the meeting. I had the facts to hand, we had a good discussion and overall it was a friendly, informative discussion. So the 30 second rMSSD had not done the job for this meeting. I then looked at the PS Flatline that would show when my beat to beat intervals were less than 17 milliseconds for 10 consecutive beats. Here is what the meeting looked like using the PS Flatline.

Slide2

Listening to the audio I could definitely see that this method caught moments that had me shifting into high gear. I chose this meeting because there was a point at the fifteen minute mark where my information was completely wrong and I felt the flush of embarrassment. This came through accurately in the chart. It also showed several moments where I was trying to calculate sums with an audience and I needed to shift into gear and focus. You can see on the chart different elements of the meeting I heard in the audio and my memory of what was happening.

So the PS Flatline approach seems to be much more accurate though I have to do further analysis on other meetings to ensure it is catching all of the stress trigger events. I have 10 additional meetings recorded with audio and HRV so i will start crunching those number next.

Finding the Parasympathetic Flat Line

From the start I have wanted to pinpoint the moment I was stressing out and identify the causes. I started with logging Upsets, then moved to using different devices to read Heart Rate Variability (HRV). I was always bothered by the lack of precision in how the devices give insight into HRV. They never said “you were stressed from the 15th to the 45th second.” Rather, they gave an average score over a longer and generalized period of time. I want to nail down the specific time my physiology starts and stops going berserk. To understand precisely when this is happening I have to look at  RR Interbeat intervals (pictured below) and find those periods in the readings where I have multiple consecutive intervals with very little variability.

Slide1

When in stress mode the distance between successive beats for multiple beats remains very nearly the same. This occurs when the Parasympathetic Nervous System (rest & digest) flat lines and lets the Sympathetic Nervous System (fight or flight) run the show. Here are graphs of my RR Intervals for a similar time period using slow breathing to create a calm state described in last week’s blog post and a session on an elliptical where I was exercising and my heart rate was 145 beats per minute.

Slide2

You can see that the RR Intervals vary while calm, and there is no variability at all while exercising. While running the Sympathetic Nervous System has the hammer down. In relaxation the Parasympathetic Nervous Systems is braking the machine and providing periodic slowdown. That means that even while resting and digesting our RR interbeat intervals are close to the same values for 32% of the time (red circled areas).

Slide4

When reading HRV the fundamental output is the RR interval. All analysis is derived from that one string of numbers which are simply the number of milliseconds between beats. So it is straightforward to find periods in readings where those intervals are close together. Looking at the raw data I hypothesized that the Parasympathetic Nervous System is flat lined when the variance is small for 10 consecutive beat to beat intervals.

Slide5

I then looked at how a rule of 10 consecutive intervals would work for my readings of the calm state and while exercising. The maximum number of low variance intervals in the calm session reading was 7 consecutive beats, and while exercising there was no variance in more that 5 beats. So if I gave each interval a value of “1” if it was in a group of of 10 ore more intervals with low variance and a value of “0” if it was not in such a group, the graphs of the calm and exercising sessions would be as seen below. No intervals are in a group of 10 low variance readings in the calme state, all intervals in are a group of 10 or more for exercising.

Slide6

The second half of the calculation is the definition of “low variance.” I proposed in my post on HRV and Stress Free State that 25 milliseconds was low. So I took the rule set that the I was in berserk status when 10 consecutive intervals were under 25 ms and graphed if for a meeting I participated in last week. That graph shows more of the meeting in high vibration than I remember and didn’t quite look right to me. I lowered the number to 15 milliseconds and the amount of unrestrained Sympathetic activity seemed to get too small. Not a very rigorous sensitivity analysis I realize, but I have to pick a start point that seems to somewhat resemble what I remember happening.

Slide7

 

I set the calculation for 17 seconds and the graph started to look like general stress cadence of the meeting as I remembered it. Fortunately, I had audio recorded the meeting!  So I went back and listened to those portions where it looked like my Parasympathetic Nervous System had stepped aside.

Slide8

 

In those three portions of the recording I could hear in my voice that I was in a state of high vibration. In the first case I was presenting something and I sounded unsure of myself. In the second I sounded confident, but my cadence was noticeably slower and it sounded like I was searching for words at times. In the final case I actually said “I don’t understand your question” and there was a bit of confusion.

So I have a base that I am now going to start running data through to see if I can validate the 10 consecutive beat, 17 millisecond ruleset. If it starts identifying points of stress with precision I will have a framework that can help me start creating preparation regimes for 1:1 interactions based on precise knowledge of stressor that flatline my Parasympathetic Nervous System.