Tag Archives: Muse

Muse Indirectly Crushes Meditation Training

Looking at my morning tracking routine I realized that one of the most impactful wearable devices I have used has been the Muse EEG headband. After using it for more than five months, I think that Muse indirectly crushes meditation training.

I started using the Muse EEG headband in June of this year and have sat with it 152 sessions. The data the product has given me has not been the source of value. The source of value has been that the product has helped me become a habitual meditator.

Muse indirectly crushes meditation training

Muse claims to read your EEG and give you a “calm” score. It also awards a secondary score that is cumulative as a game style mechanic to keep you coming back.

When I started with Muse I took a straightforward sporting approach to the mediation training.  I would practice each morning with a goal to get higher “calm” scores. I saw it similar to training for a 5K where I would look to my speed. The fun would be to see how much higher I could push my calm score with practice.

Unfortunately, it did not work out that way. I did not improve the score even with months of  practice.

Muse indirectly crushes meditation trainingThe calm score itself is of questionable usefulness. It did not correlate with any other physiological factor that I compared it with. For example, when looking at the correlation between the score and heart rate variability (HRV) across 145 readings, there was no relationship (Pearson r = -.016). I had taken HRV readings simultaneous with the Muse readings and they did not track together at all. Blood glucose levels (r= -.17), average resting heart rate (r = .13), blood pressure (r=.21) all were at best a weak relationship.

Thinking that the calm score might somehow be associated with how distracted or stressed I was, I looked at a morning mood score I had been keeping versus the calm score. Oddly, I found a moderate inverse relationship between the Muse calm and my perception of mood (r = -.32). That meant I was more “calm” when I was in a lousier mood that morning. That made no sense at all.

So my original idea of practicing to increase my calm score did not pan out for me.  So why do I believe Muse indirectly crushes meditation training? Because for me, meditation had been boring and numerous attempts in the last 32 years to incorporate it in my daily routine had failed miserably. Chasing the Muse score in a structured way each morning I broke the boredom and acquired the habit of meditating. And meditating has scientifically validated positive benefits.

The Muse basic session is six minutes long with a starting calibration of one minute then a five minute reading. After multiple months of starting doing these simple six minute readings with the headband I found I had started comfortably expanding the amount of time I was sitting quietly.

First, I incorporated a ten-minute session before the Muse session to test the effectiveness of binaural beats, and that ended up with me sitting quietly for fifteen minutes each morning. Then a podcast on HRV inspired me to add twenty minutes of paced breathing later in the day. I was able to expand because I had gotten comfortable with sitting during the initial months of short six minute Muse sessions.

So the paradoxical outcome presents itself. In the past when I had tried to “learn” to meditate I could not do it for long and was unsuccessful. When I introduced the game of chasing the Muse calm score I was able to get enough time sitting quietly to find meditation doable and even pleasurable. And when I had enough data to determine the score I had been chasing was meaningless I had worked my way up to 35 minutes of sitting a day. That is why Muse indirectly crushes meditation training.

I imagine the engineers who created the scoring system and the EEG technology may not appreciate my assessment. It seems better to have the scoring and EEG technology to be a valued feature. However, the product bills itself as a meditation assistant. In that, it performs its job perfectly.

To someone looking for a Quantified Self product review on Muse the answer may sound like something out of a wearables zen koan. To realize the value of the Muse product, diligently try to improve your Muse score until you are sitting in comfortable in daily meditation realizing that the score never was the point.

 

 

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Water Fast Yields Ketosis And Halitosis

I am a regular listener and a fan of Damien Blenkensopp’s The Quantified Body podcast. He podcasted excellent coverage and reportage of his five day water fast so I decided to try it and report back to compare and contrast my experience.

Before the fast I was intimidated by the idea of doing it. Despite hearing evidence from Damien’s experience, I had the idea that I would be in a stupor for five days. I also envisioned that I would have hardcore hunger pain.

man2andemptyplate

I had an embedded fasting advantage and simultaneous disadvantage in the fact that during my military days I attended and graduated from the Army Ranger School. Small ration amounts and long patrols allowed me to experience true near starvation and the associated pain that goes with it. I remembered those pains and dreaded experiencing them again. I was pleased to find the fast was in no way as stressful as Ranger School.

Ranger School Pic

During the fast I took about 3 liters of water a day and had no other liquid or food of any type. Not a single cheat. The closest I came to opening the glove compartment in the car and seeing a box of Tic-Tacs. I resisted though I had lust in my heart.

Why I did it

Other than being inspired by The Quantified Body podcast, I have been trying to test my food and supplement intake to drop my blood glucose levels. I thought a fast would be a way to see my glucose and ketones in a food free state. And I liked the challenge of it.

What I measured

For the fast I measured:

What I Found

Overall, I found that fasting for five days is not stressful, does not put me into a stupor and my glucose level dropped to a range Damien and his co-fasters reported seeing. As a technique, a water fast yields ketosis like I had never experienced before. I lost 10 lbs. And I had horrible bad breath for four of the days. Here are the details.

Heart Rate Variability

My heart rate variability (HRV) averaged an rMSSD of 44 during the fast and my average over multiple months prior was 50. The lowered period on the graph just prior to the fast was due to travel.

1. HRV&Fasting

Glucose & Ketones

Fasting glucose clearly dropped from an average of 101 down to 69 for days 3, 4 and 5. Of interest is that it took my body two days to adjust.

2. WakingGlucose

It took me the two days to bring my ketones up to a point where they were more plentiful than my dropping glucose. I had three days of the glucose-ketone ratio being under 1.0, which reportedly has a therapeutic effect. This was a great outcome. Here are my afternoon (postprandial) readings:
3. Glucose & Ketones

Weight

Obviously weight was going to drop as I was not eating. I was an average of 192 pre-fast and lost 10 lbs by the end of the fast.

4. Weight

Here is a before and after picture that shows for me what losing 10 lbs looks like. Picture on left was the night before the fast, right the last day of the fast.

Fast Yields Ketosis and Halitosis

Awake

Nine times a day I measured how alert I felt because my story was that I would be in a stupor. A measure of 3 is normal, 2 would be actually yawning. You can see I was yawning tired in the first few days then my body compensated. I was never exhausted.

6. Awake Readings

Hunger

I felt hunger pangs throughout but intermittently. Only once did I have a headache related to the fast which was the end of day 2. Notably day 3 on my awareness of hunger diminished and you can see the jump in scores (higher is less hungry).

5. Hunger Graph Fast

Muse Calm

My Muse calm score seemed to drop off through the fast. I felt calm and good each morning on waking you can see the drop when the fast started. Bears further investigation.

8. MuseCalmFast

Blood Pressure

My diastolic blood pressure was completely unaffected and my sistolic popped up a bit on days 3 & 4.
9. Blood Pressure

Notes On The Experience

My original idea was to have a five day period to focus on the fast and be sequestered away to save energy, but life intruded. I had several social commitments that had been scheduled well before I decided to do the fast to include a Meetup and a charity event.

One significant drawback is my breath was awful. According to Damien and his fellow fasters, this is due to increased acetone that comes out through the breath. When you are discussing deep thoughts at a charity event while spewing breath that can knock a buzzard off a manure wagon you have discovered the downside of fasting.

Anecdotally I felt great when I was focused on a task and was able to get a lot of work done. But when I was interrupted or had a something suddenly come up I experienced fairly hot and palpable irritation. This seemingly lowered ability to handle context switches deserves further study.

This is the most meaningful and impactful experiment I have done. I ended the fast having experienced the fact that our bodies have a deep reserve of nutrients and that eating huge meals three times a day is completely unnecessary. Doing this has raised my interest in finding my own optimal nutrient level. Thanks for Damien for the inspiration. Good times ahead.

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.

 

 

Randomized Test – Booze Amount vs. HRV

After my last Booze test I wanted to find out the limit of how much alcohol I could drink and have it not impact my Heart Rate Variability (HRV), Muse % Calm score and Glucose level. In a scientific study I had seen that 2 drinks is a limit of what men can drink and have it not effect their HRV. I thought I would give it a whirl by conducting a randomized test.

martini

 

My Question

If I have three alcoholic drinks in an evening does it significantly change my morning HRV and mental calm readings?

What I Did

For twenty days I would either drink three drinks in an evening, or none. To ensure this was a randomized test I used a randomly generated instruction for which days I would drink and which I would not. It made for some funny Tuesday evenings and some less than social Fridays, but science must be served.

How I Did It

I used a Google Spreadsheet to generate a random list of instructions for the twenty day period with an output of “zero” or “three.” Each evening I would either have the drinks or not.

The following morning I would measure my mental calm using Muse EEG headset and my HRV using a Polar H7 heart rate belt that sent data to an app called the Heart Rate Variability Logger. All data went into the same Google spreadsheet.

At the end of the twenty days, I separated the lists into two arrays based on the amount of alcohol and ran a T-Test using the Google Spreadsheet. For days where there was an unusual circumstance (odd food consumption, travel, drinking neither 3 nor 0) I threw out those measurements.

What I Learned

Drinking three drinks in the evening does not significantly affect my HRV, % Calm or Glucose levels the following morning. After separating the data and running the T Test, here were the resulting p values:

Measure p values
HRV 0.326
% Calm 0.551
Glucose 0.529

For any of the measures to have been significantly impacted the p value would have needed to be .05. So I found a level at which I could have a social drink and not impact my physiology significantly. Anecdotally, on the mornings after 3 drinks mornings I felt fine so my experience matched the results.

Launching QuantXLaFont

I have had enough people ask me how to start doing these studies that I have created a site specifically to help people do these types of N=1 studies. You can get the basic instructions absolutely free and can pay for coaching if you would like. The mission is to support people in taking their own data and testing the dimensions of their own unique physiology.

 

Measuring Muse Mindfulness vs HRV

The more experienced you get with taking your own measurements you will find that even the smallest technique change can alter readings. A wary Quantified Selfer will be aware of this and control for variation. I found this when I measured Muse Mindfulness vs HRV.

Early in my self-measuring career, I discovered that real-time data can cause a stress reaction I called Freakback and I even tried to describe its  anatomy. When your reading is telling you that you are not relaxed you try to force relaxation and that causes stress which raises the stress reading. Eventually the amplitude of stress reaches “not inconsiderable discomfort.”

Each morning I measure my heart rate, EEG, glucose and ketone level. From these readings I get the measure of how much energy I have for the day ahead and can see the impact of the previous day’s activity and sleep on my physiology.

Muse Mindfulness vs HRV

My Question

When taking my EEG and heart rate, is it better to take the readings simultaneously or have one precede the other?

The Resulting Potential Action

Based on the result I would alter my morning meditation session to either take the heart rate and EEG reading together or  take one reading before the other. This resultant technique I would consistently use to ensure any variability came from external factors rather than my changes in data gathering technique.

What I Did

To measure my heart rate I used a Polar H7 heart rate belt, an iPhone6 and the Heart Rate Variability app. The output was my resting heart rate, rMSSD, Low and High Frequency of Heart Rate Variability (HRV).

For my EEG, I used the Muse headset connected to an iPod5. This gave me a %Calm score after taking a baseline of active thinking.

First, I took readings simultaneously for 15 mornings. This meant I calibrated the Muse, turned on the HRV reading then breathed rhythmically using a breath pacer. At the end of 5 minutes I had both readings.

Next, I took the Muse readings first, then HRV for 10 mornings. The difference here is that during the Muse readings I was counting breaths with eyes closed, during HRV I using a breath pacer. So my method of concentration was different unlike the simultaneous readings.

Finally, for 13 mornings I switched the order with the HRV session first and the Muse session following.

After each session I entered the values manually into a Google spreadsheet for analysis.

What I Learned

The most efficient way for me to measure my EEG and heart rate in the morning is to conduct the readings simultaneously.

Because I could only look at correlations rather than causes in this study it was important to me that when I was calm and balanced the two readings would show some consistency. For example, if I had a poor nights sleep I would think that my %Calm and rMSSD readings would both be lower. So the correlation of the two readings was important to me.

Taking my HRV and %Calm reading at the same time had a strong positive relationship as you can see here from the Pearson correlations:

  • HRV before Muse; r = -.14 (No relationship)
  • Muse before HRV; r = -.77 (Very strong negative relationship)
  • HRV same time as Muse; r = +.48 (Strong positive relationship)

The other methods show interesting differences in readings based on a variance in technique. It seems logical that an upset physiology would show low readings in the same 10 minute period. Or vice versa.

Instead when I shifted from simultaneous readings to using Muse first, there was a very strong negative correlation. That meant when I had a session with a high %Calm EEG reading a lower HRV would immediately follow. Or when I was thoughtful and had low %Calm my HRV was higher. I am open to comments on why that may be. It is a unique outcome that needs further testing as there may some interesting things going on.

When I took the HRV reading before the Muse reading there was no relationship. Somehow that sequence of reading scrambled the signal because there does seem to be a relationship between %Calm and rMSSD when read at the same time. So I have discarded that technique.

As a quick check I compared the average %Calm reading with an average scaled rMSSD (translating it to a scale between 1 – 100) for each of the three techniques. Here is the result:

Muse Mindfulness vs HRV

The average rMSSD was close across the board (45 – 51%) but the %Calm was much lower for the HRV before Calm and much higher in Calm before HRV. Some ideas for this may be that the time pressure of wanting to complete the reading and get on with my day may impact the mindfulness. But that is for further verification.

So with these results I will use Muse and my HRV apparatus simultaneously to measure the waking state of my physiology. I will set up the process so it is automatic and consistent, and begin testing external influences on the morning state.

Booze, HRV and Muse

I’ve become interested in finding with greater precision how my body reacts in different circumstances. I had a story that I felt poorly after eating cheese. It was based on one period of my life and was entirely anecdotal. As I described in my post about my shift to a ketogenic diet, I had started eating more fats, to include cheese. And I felt great. This got me thinking about how many of these unexamined stories guide my behavior.

With that in mind I started looking at alcohol’s effect on waking mental calm and heart rate variability (HRV). I like a glass of wine or two in the evening. It is well documented that alcohol has a physiological impact. From quantified selfers looking at their Basis data to scientific studies there is a wealth of information on the physiological impact of alcohol. My question is how much can my body tolerate before it reduces my heart rate variability and mental calm.

Booze, HRV and Muse

My Question

What impact does having alcohol (or not) have on my morning HRV and mental calm?

What I Did

For thirty-three days on waking I measured my mental calm and heart rate variability while noting if I had had alcohol the night prior.

How I Did It

I would measure my mental calm using Muse EEG headset and my HRV using a Polar H7 heart rate belt that sent data to an app called the Heart Rate Variability Logger. All data went into a Google spreadsheet.

What I Learned

Drinking alcohol the night prior reduced average HRV and increased average Muse “% calm” score. After a night of boozing I was mentally more Zen but my nervous system was under increased load.

The Muse % calm readings were not visibly different between having had alcohol or not. The Pearson correlation (.12%) showed a negligible relationship between the calm readings and whether I had consumed alcohol the night prior.

 

Booze, HRV and Muse Booze, HRV and Muse

 

My average % calm after having no alcohol was 36.4% and after having alcohol was 42.7%. Looking at the averages I appeared more calm after drinking. Because the scores did not correlate with consumption we can’t draw any real connection.

My HRV did correlate with consumption, with a Pearson correlation = -.306, a moderate negative relationship. There seems to be a connection with drinking alcohol and a lowered HRV was lower the following morning.

Booze, HRV and MuseBooze, HRV and Muse

 

My average rMSSD the morning after a night of alcohol was 48.6. A morning after no alcohol the average was 62.1. A moderate correlation and a much lower average verified that HRV seemed to be impacted by alcohol.

But knowing that does not really give me any precision nor any guidance on how to change behavior. So my next study is to examine how much alcohol I can consume and not have my HRV drop. If I am going to enjoy a glass and don’t want to take an HRV hit the next day, how many glasses can I have?  With this I will know my own tolerance and be able to guide my actions with better data.