How Meetings Go – Physiologically

I have been measuring my rMSSD during work meetings to see what factors impact my performance when engaging face to face with others. I recently had two meetings with the same group of people on the same topic about a week apart. Before each meeting I also took my blood sugar to see if there was any information to be gleaned there. Here are the charts:

Slide1My blood sugar was abnormally high at 135 before the first meeting. I can’t account for it as I had salmon for lunch two hours before. My average rMSSD was much lower at 28.7 which is a reading of high stress. My stress point for rMSSD is 48, when I am below that reading it is an indicator that I am in stress. My experience during the meeting was of being overly excited and I breathed regularly during the meeting.

During the second meeting I was careful about my food choices for the day and had a good blood glucose level of 105. My average rMSSD for the meeting was higher at 38.8. I felt more in the zone in the second meeting physiologically. We were digging into more details in the second meeting and I felt challenged at a few points, and you can see where the reading drops to a very low rMSSD at a few points.

If asked I would have said the first meeting was more successful based on the discussion. And I would have said the second meeting was more challenging. However physiologically the second meeting was far less stressful than the first. When less stressed I imagine my actual performance was better. So my perception of the outcome was very different than the physiological reality.

Next step is to measure outcomes and see if the results correlate with the physiological state occurring during the meetings. I can’t rely on my perception of the situation so further readings will determine outcomes with physiology.

Blood Glucose, Heart Rate Variability and Face to Face Interaction

My Quantified Self Lessons Learned in 2014

I started the year wanting to explore how I could use technology to understand when stress was or was not occurring. I was interested in if self reported stress was reliable and if there were techniques I could practice that would reverse stress in increasingly shorter periods.

Looking for technology that could help identify when I was stressed was an exercise in buying a lot of technology and trying to find anything that would actually work. I looked at galvanic skin response, different watch iterations and ended up settling on heart rate variability (HRV) as a way to understand when I was relaxed or stressed.

As I began looking at different states of stress using HRV I measured myself while meditating, getting a tooth drilled at dentist, while giving a public speech, and getting a haircut. Each of these gave me the range of when I was stressed and not and gave me a baseline for further studies. I think the takeaway here is the boring baseline building work is necessary for real insight.

I learned that when it came to returning to poise from a state of upset, I could improve with practice and that a key technique was respiration. The ability breath well, which takes a bit of practice, was the key to busting stress. So stress, like fitness, was a state that could be altered with progressive practice. That was my assumption at the beginning of the work.

What was less obvious was how much thought and belief plays a part in how much stress I experience. Early on during my self reporting studies I found that a surprisingly high percentage of stress was self induced. Most stress was due to a discrepancy between what I thought was proper and what what happening. Even deeper, I found that my reactions were not complex reactions, but that emotion is navigation. Whether I was feeling in the right location or out of place determined whether I was calm or stressed.

I thought I could use technology to measure stress then solve for it through techniques, but that model turned out to be incorrect. It turns out my thoughts drove a stream of stressful reactions (or not) and that knowing when I am in a state of stress or not helped me change the underlying construct. And that is what takes me into the new year.

My Quantified Self Gear 2014

I have steered clear of reviewing products because I think simply buying products has very little to do with Quantified Self. And I thought it good for me to review what I used and how useful some of it was. My premise for my QS work in 2014 was to use technology to train myself to be happier.  I had used several Garmin products to successfully train for a half Ironman. Why couldn’t I train myself to be happier?

I pulled everything out of my wearables storage drawer and took this photo of everything I bought in 2014:

QSGear

The items:

I started with a Pebble smartwatch that my wife had given to me as a birthday gift. $99 from the original Kickstarter campaign. I love it and still use it daily with one app called Motiv8 that tracks activity.

Google Glass. What can I say. I fancied myself as an Explorer with $1500 burning a hole in my pocket. I once looked up the population of the state of New Jersey on it and sent my son an email saying “Hi this is my talking to my Google Glass.” That about sums it up. It has not been charged up for about 8 months now. It was so deep in the drawer it did not make the picture above and I just now remembered having it. Enough said.

Zensorium’s Tinke. Billing itself as a stress and fitness measurement device, I purchased one at the Quantified Self Europe conference in Amsterdam for over $100. Its readings made no sense to me and it went into the drawer pretty quickly.

Heartmath’s emWave2 & emWave Pro. This was over $400 worth of gear and if you follow this blog or my QS speeches at all I did get a lot of use out of both products. I conducted multiple experiments and accrued 183,843 “coherence points” – which is quite a few hours of cardiac coherence. In the end I grew out of it as coherence was not my ultimate goal. I think this product is way overpriced and was useful.

Neurosky Mindwave & Mindwave Mobile. Over $200 in cost, I could never get either headset to work consistently. I took some readings but any attempt to get the devices to reliably produce output was frustrated by bluetooth connectivity issues  of some sort. A big disappointment from Neurosky.

Emfit sleep monitor. I met the Emfit team at the QS EU conference and they helpfully offered me a free trial of their product. A combination of wireless connectivity issues and my move from London to San Francisco resulted in my never getting it working.

Mio heart rate band. Very slick implementation and a comfortable wrist band that uses pulse oximetry. I loved the idea, and it was not useful for heart rate variability experiments. The accuracy was not good enough so into the drawer it went. I paid over $100 for it.

After visiting with a friend who worked at Basis I dutifully bought the first version of the watch for around $150. I liked a lot of the ideas but did not really take to the interface or the gamification element of the online account. By the time I bought it I had eliminated pulse oximetry as reliable source of heart rate data. I gave it to a friend and he likes it.

Fitbit flex. I ended up buying two for $99 each because the first one gave out and stopped charging. The second one was spotty on charging as well. I used the product for 10 months and got a lot of value from it. In the end, the inability to charge it and a policy change that eliminated active minutes as a goal had me put it in the drawer. I replaced it with the $79 Garmin Vivofit because I do like to monitor my daily activity. So far that seems to be working out.

Sweetbeatlife & the VitalConnect Patch. Sweetbeat Life is an app that takes heart rate data from either a belt or the VitalConnect Patch. The patch seemed novel as it was convenient and comfortable. And it did not stay adhered on my chest for more than a few sessions. It was a breathtaking $199 for a set of 10 patches. I did not understand the real cost until the first patch fell off after the second use. Really cool and really expensive. I went back to the old reliable Polar H7 heart rate belt for a nice price of $80.  And one belt will last the whole year.

One thing that is not clearly stated is that you need top end smartphones to use apps associate with all this hardware. Neurosky, Fitbit, VitalConnect Patch and even my much loved Pebble need a phone with Bluetooth LE. I had an older version Android phone without Bluetooth LE so I needed to buy an iPod5 for iOS only apps and devices $199. And for Android I had to buy another device with LE so I bought a Nexus 7 tablet for $245.

So a quick add up gives me approximately $3,500 worth of gear of which 42% of that is the Google Glass. What did that expenditure do for me? It taught me through brute force that picking an area of Quantified Self to study and focussing there is 90% wikipedia work and networking with other people who have knowledge. 10% is hardware. And ultimately the majority of value came from about $500 worth of the gear I bought (Heartmath Pro, Polar H7, iPod5). The rest helped me understand some things but were not good value for money. For the Quantified Self, as in life, money cannot buy you happiness.

My Quantified Self 2014 in Review

I had a good Quantified Self year this year. As a long time logger and casual athlete I have always logged my personal data in some form. This year with the support of the Quantified Self community I was able to explore two specific areas. First, I moved stress tracking from self reporting to the use of wearable devices. Though I bought a few more devices than I would have liked I found that heart rate variability measurements using $65 worth of equipment was sufficient to track stress. Second, I was able to pull out insights about consciousness and heart rate variability that set the stage for future studies.

I explored 20 ideas this year that I organized into five umbrella studies. I started looking at the data I had collected through self reporting of “Upset Events.” I followed that up with a look at Upset intensity given different situations. After seeing the limits of self reporting I started using different devices to measure stress, settling on Heartmath used during working session. Using the device I discovered Freakback can have an effect on results. After learning how to work through that I completed a first study on how I recovered from Upsets.

As I was conducting these studies I had an emerging idea that emotion is navigation. The regularity of emotional shifts seemed like “sighting” as I worked through different ideas. As I worked on this idea I found that Heartmath was too limited in what it measures. Heart Rate Variability has a more direct measurement in rMSSD. I dropped Heartmath and started using Sweetwater HRV’s SweetbeatLife to monitor rMSSD. Using this tool I started measuring stressful events like getting a tooth drilled and firing a shotgun. I played with machine learning and straight statistical regression and determined my “stress point” when read by rMSSD. This provides me a tool to study a variety of situations going forward.

Along the way I gave five Quantied Self meetup talks, 2 in London, 1 in Amsterdam and 2 in the Bay Area. In London and Amsterdam I did my talk We Never Fight on Wednesdays, and in London my followup Don’t Just Stand There. In the Bay Area I presented my talk Every Other Minute where I talked about the navigation impulse. And finally my Bay Area presentation on heart rate variability and Flow. These talks went well and I am set up to give a presentation at the QS Global conference (QS15) in June.

Some of the 20 ideas did not pan out. My work on 800 numbers went nowhere. Ideas about reading my heart rate while doing The Work by Byron Katie did not have sufficient detail to be interesting. Several other ideas blew up on the launchpad. However, I’m pleased with the progress this year. In my next post I will talk about the lessons I have learned during this work.

Heart Rate Variability & Flow Presentation @ QS Bay Area Meetup

Glucose & Heart Rate Variability

My sister-in-law is a doctor and follows my Heart Rate Variability (HRV) adventures. She suggested that I look at my glucose levels and see how it effects HRV. My first step was to buy a glucose monitor and I was somewhat uncomfortable with the idea of drawing blood daily. A trip to Target to buy an Onsync glucose meter was pretty easy and the blood drawing process is far less uncomfortable than I thought it was.

So I started pulling my glucose each morning when I got up. Immediately afterward I took my HRV focussing on rMSSD using the Polar H7 and Heart Rate Variability Logger. I took a reading for 1:30 with three 30 second readings which I averaged out for the session. While taking the reading I used the Paced Breathing Android App. After I was completed I entered the glucose reading and rMSSD in an excel spreadsheet.

Here is what I found.  Glucose levels have a strong negative correlation (Pearson value of -0.4) with HRV. That means higher blood glucose had a strong relationship with lowered HRV.  That means eat food that jacks your blood sugar and your are less responsive to your environment. Eat candy and be dumber when talking to your boss.

Here is a graph of eight readings:

GlucoseReading

Looking at the figures you can see that generally my glucose level averaged about 104. When I fasted (12 hours of no food) it dropped below 100. The rMSSD was between 55 and 78, all well above the stress line. So my morning readings showed no stress and normal blood sugars. What it also showed was a strong correlation. So measuring before and after daily events will give more information to see if I really am dumber talking to the boss after eating candy.

V1bes on Indiegogo

I met the founder of V1bes, Gustaf Krank, at a wearables gathering in Helsinki last year. He gave a dynamic presentation to the conference and afterward walked me through the technology with a personal demo. The approach is like no other in that is aims to pull together multiple electromagnetic signals from brain, heart and the environment through a ring.

V1bes has launched an idiegogo campaign. I am going to to get one to see how its measurements correlate with Heart Rate Variability (HRV). The idea of electromagnetic “smog” as an influencer of HRV is something worth looking at. Unlike HRV Gustaf’s invention does not have the large number of medical studies with which to compare but that is part of the fun.

Managing Imagination

Since April of 2014 I have been posting my findings here as part of a systematic way to understand and mitigate Upsets. I logged Upsets as they occurred, measured my heart rate variability during periods of stress and connected types of Upsets to different types of thought.

The first real insight that came from self reporting Upsets was that the majority of them were Self Induced and of those the majority were anticipating future negative events. The fundamental tool we have which is the ability to imagine a future scenario is the source of most of the stress – thoughts that anticipate a negative future outcome.

Another insight is the volume of thought. Thinking I was capturing a high number of Upsets in my reporting was completely blown apart by watching how often my physiology altered based on thought. Was looked at the beginning to be a 5 to 8 time a day volume was actually up to 450 thoughts a day that could potentially cause Upset. And that volume is constant. So any plan that includes eliminating thought is irrelevant. The plan must be based in how I respond to Upsets.

Looking at the lessons learned the core skill to develop is managing imagination. Imagination is our engine of progress, it shows us what is possible. It is also the source of what we believe are our misfires, misalignments and Upsets. Believing too much in imagination immerses us in our miserable misfires. Completely eradicating imagination robs us of our ability to be motivated, plan and progress. Somehow we have to find a middle ground of practical imagination, a place where we see what is inspiring and possible while knowing when to discount those scenarios that are impossibly negative and exaggerated.

Dual-3-Back & HRV Update

I have continued the experiment I reported earlier on playing Dual-n-back game while monitoring my progression Heart Rate Variability (HRV). I have manually set the game to Dual-3-back, meaning I have to remember a location and letter that is three iterations in the past. For a full explanation of how much cognitive load that adds to the situation you can read Gwern’s FAQ on Dual-n-back here. I can tell you from experience that 3 back is a lot harder than 2 back. The data shows the difference in scores:

Slide1

 

You can see I was reliably getting percent scores in the 70’s and 80’s playing 2 back. When I increased the difficulty to 3 back my scores dropped to the 30’s. An you can see a progression where the most recent plays are moving toward 50%. How has this effected my HRV? Here is my rMSSD for the last 8 sessions of 2 back and first 19 sessions of 3 back.

Slide2

 

As I have reported before an rMSSD above 48 for a 30 second reading occurs when I am relaxed and feeling stress free. Each of these games are 4.5 minutes long, so that is 9 consecutive 30 second readings. You can see the 2 back games toward the end were averaging above 50 so I was feeling stress free during those sessions which makes sense because I my average score for those sessions was 77%. I had the feeling of having mastered that level.

When I started with 3 back  the rMSSD dropped to an average of 43.3 for the first ten sessions. 3 back was definitely harder and I was seeing very slow progression in the scores. I recall feeling a bit negative about the process and unsure if I could get better at the task. I did not really try any strategies, I just tried to improve through repetition.

The last four 3 back sessions are interesting. At session fifteen I was thinking about how to move the score I decided to try focussing on only the location and “wing it” for remembering the audio cue. To my surprise BOTH measures went up. I saw better results and got interested about pushing this strategy. For the following sessions you can see both my scores and my rMSSD going up. My rMSSD average for those sessions is 54.25. I was enjoying the process because I saw there was a path to improvement.

What is intriguing is that my rMSSD (and stress) changed not as a result of the scores, but at the specific point I felt I had discovered a way to improve the process. My perception alone drove the change in HRV. My story about improvement and efficacy moved my stress level, not the performance of the game at all. So growth and learning is gradual, but our story about how the progression of the learning can be more dramatic.

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