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.


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


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


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


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.

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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 it. 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.



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.

My custom survey to rate how big a boost the caffeine had on my workout, using the QXL DIY Tracker.
My custom survey to rate how big a boost the caffeine had on my workout, using the QXL DIY Tracker.



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.

An overview of my September data, focusing more on just the caffeine intake before a workout.



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.

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.

This was me, but playing basketball. This could be YOU: rock climbing or _____________.

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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?


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.

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.



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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.



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How Brain.FM can transform the way you work, sleep, and meditate

This past Monday I was introduced to a new app that I have since experimented with this week and have already concluded will change the way I work. It takes 30 minutes to try, is free of charge, and for you too, it may also change the way you sleep or meditate.

The app is called Brain.FM and my first exposure to it was by attenting a Chicago Biohacking Meetup and hearing about it straight from the founders, Junaid Kalmadi and Adam Hewett. Their overall goal is to cure ADD, anxiety, and insomnia through their digital health app that emits audio brainwave training. The sessions are analyzed and EEG tested, with much of it coming from Northwestern University neuroscientist Dr. Giovanni Santostasi. His published results are here.

Their data has been further grounded by over 12 years of research, working with 35,000 customers, and over 180 studies conducted to continue the growth of audio brainwave technology across this time.

The information and their backing are both important to know before trying Brain.FM for the first time without any skepticism. I had the advantage of hearing both founders illustrate their passion and belief for Brain.FM in person. So needless to say, I was excited to try it for the first time during the rest of my work week. Here are my first impressions and a walk through of how to use Brain.FM.

Screen Shot 2015-09-16 at 5.03.11 PM

The first great thing about Brain.FM is that it allows you to try it for free. So while you’re reading this, I suggest you follow along and hit the Focus option of the 3 that you’re initially presented above.

As you can see, the app can cover a lot. My primary interest is to improve my work efficiency so I used 3 of my 5 free sessions on Focus — two on ‘Intense Focus’ and one on their other subset of ‘Relaxed Focus’ to see the difference.

Screen Shot 2015-09-16 at 4.30.45 PM

The comforting pop-up illustrated above again underscores the research and testing behind the brainwave session. It turns out, “Benefits should be realized almost immediately while listening to this session,” was 100% accurate as well.

You see, I’ve been searching for a new form of an audio compliment lately. I used to be able to work with hip hop or R&B in my headphones, and most recently podcasts, but I’ve found this summer that I am more easily distracted to the words and this slightest attention switch throws me off my focus. With Brain.FM, I was greeted with a 30 minute continuous instrumental that featured a calm, almost march-like melody to go along with a variety of orchestral or percussion layers. The sound wasn’t too complex and actually reminded me of the old computer game Age of Empires. If you played that game too, you can instantly think of the brooding instrumentals that accompanied your rising empire. I felt the motivational nostalgia, that’s for sure.

After the 30 minute session, I was prompted by another cool feature of Brain.FM — a survey intended to build your own personal, unique brian profile. Answer questions honestly about not only your focus, but anxiety, mood, stress, and sleep and Brain.FM will calibrate a sound that works best for your needs.

Screen Shot 2015-09-16 at 5.02.09 PM

I underwent one more ‘Intense Focus’ 30 minute session afterwards and proved that the productivity of the first one was not a fluke. In fact, I started writing this post in that session!

To further test the app, I tried a ‘Relaxed Focus’ session while doing less pressing work. The instrumental was, naturally, more calmer and slower than the ‘Intense Focus’ track. I felt immediately transferred to the same zone as before, but this time I was only able to sustain focus for the first 20 of the 30 minutes. Then I was back to browsing my Twitter feed… so I’ll probably be sticking to what worked for 100% of the time: ‘Intense Focus’.

Next, I tried the ‘Sleep’ track last night. I usually have no trouble sleeping but when I was tossing and turning for 10 minutes, I decided to put my headphones in. Once again, there is an instaneous transplant inside your mind. You’re encouraged by Brain.FM to let your mind wander a bit and I did as I first noticed the sounds itself: a soothing thunderstorm in the distance combined with slow, wavy layers of strings.

I had to round out the capabilities of Brain.FM and test the ‘Relax’ feature as well. I didn’t use it to meditate but I did take a stretching break with the soundtrack in my headphones and again immediately felt a change within. This time, I noticed a sense of relief, like a weight had been lifted off my shoulders. Within 1 minute, I felt more air flowing into and inside my body with each breathe. These tracks are 15 minutes long and I intend to combine them effectively with the ‘Focus’ sessions.

* * * *

By now, you can see that my first impressions of Brain.FM are more than favorable. I want to sign up beyond the free sessions now and test the app more with my productivity. Right now, I can apply the same DIY Tracker that I used for my Coffee Intake QS Experiment and click the option for “A very high boost.”

Taking it a step further, it would be interesting not only to see black and white results in one’s productivity but also to track your vitals and see how it flows during a session. I told Paul about Brain.FM this week too and he’s already experimenting with the app for more data along these lines. Look out for his impressions and takeaways in the coming weeks.

Brain.FM presents at the Chicago Biohacking Meetup 09.14.15
Brain.FM presents at the Chicago Biohacking Meetup 09.14.15

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Disappointing Outcome With Bitter Melon Protocol

This is an N of 1 study on a specific supplement that reportedly has the outcome of lowered blood glucose levels. In June of 2015 I went on a ketogenic diet. I was enjoying the benefits of weight loss and increased alertness, but I noticed my blood glucose was creeping up in the daily readings. I wanted to see if I could turn that around and bring the readings lower.

I heard on the Ben Greenfield Fitness podcast that Bitter Melon lowers blood glucose levels. I purchased the supplement and decided to test it. The results were surprising, but not in a fun way.

suprised scientist

My Question

Is Bitter Melon effective for in lowering my blood glucose and should I continue to take it?

What I Did

I took Bitter Melon on a randomized schedule for 20 days, then took it every day for another 14 days. As I did so, I recorded my glucose levels after waking, at 10am, and 3pm each day.

How I Did It

I used a Google Spreadsheet to generate a random “one” or “zero” for each day in the 20 day randomized period. This gave me instructions on whether or not to take the Bitter Melon. After 20 days, I took it every day for 13 days.

The daily dose was two tablets, which is 900mg of the supplement. I excluded readings on days where food intake was outside of a normal range, or something extraordinary was happening like a flight or no sleep.

At the end of the period, I looked at the difference on the randomized days using a TTest. I also looked at the effect on my glucose for the period where I was taking the supplement every day.

What I Learned

I had a disappointing outcome with Bitter Melon protocol. There was no change in the continued climb in my blood glucose levels. This graph shows the period from the beginning of the diet to the end of the Bitter Melon test:

Morning Reads

The period of taking Bitter Melon was from 8/9/2015 onward, so for me it appeared to be ineffective in arresting the upward movement of the glucose levels.

The first measure I looked at was the morning readings based on having taken the supplement the day prior. There was no effect: p=.84. Recall that to have demonstrated a significant difference in the two data sets we are looking  for p<.05.

The second measure was a 10am reading after having taken the pills at around 7am. Doing the TTest comparing the days where I had taken the supplement vs. not there was no effect: p=.25.

The final measure I compared was a measure at 3PM, comparing the days where I had ingested Bitter Melon vs. not. The test showed a significant difference (P=.057), but the result was reversed from what I would expect. The average glucose reading on the days I took Bitter Melon was higher than days I did not take the pills. That is an odd outcome.

Finally, looking at the effect of taking the supplement daily there was no significant change in the morning glucose level taking an intermittent dose versus a daily dose (p=.17).

image (7)

As a result of this analysis I will no longer take Bitter Melon and save myself the money. And the data opens up another line of research. Something is driving my glucose levels upward. I am tracking my food intake and my carbohydrates are very low. I am not eating any processed foods. The next step is to eliminate all supplements and see if the source is there as well as up my fiber levels. One thing is for sure. A “one size fits all” ketogenic diet ripped straight from the podcasts is not the cure all for my physiology. Nor is it probably for yours either.



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The future of quantifying our memories

The short answer to the headline: a new app called Compass.

But first, let me explore how I got there.

This week, I’m taking my weekly writeup in a different direction (no pun intended.) A few of my recent quantified self experiments are simply requiring more time and data to evolve. I am still tracking my coffee intake before working out, and now I’m starting to gather more Moves data from those actual workouts. I can begin to see new conclusions forming, but am still stuck with a small sample size.

This limbo phase inspired me, however, to reflect to a time earlier this year before I had all the new tracking apps on my iPhone 6 upgrade. How else have I conducted my own quantified self experiments? What old data can I uncover?

Then it hit me: I have actually been tracking my travels for years. Thanks to Facebook.

I know this isn’t some revolutionary “light bulb moment” here. The majority of us are already aware of Facebook Places. Past check-ins and geotags on photos are aggregated into this data map below and you can sort your places by most recently visited and cities as a whole.

But today for the first time I viewed my destinations in a quantified self lens. Here are a couple of conclusions I easily arrived at: there are still so many cities in the U.S. I want to see and OH YEAH, I need to travel out of the country!

This is literally the entire world I’ve explored with my own eyes. I don’t even have a passport. But onto my next point…

The other cool feature of Facebook Places is if you hover over one of these data points, it pops up photos taken from that city. For example:



So this begged the question: Where can we go from here with this data? It’s nice and heartwarming to revisit memories from places we visit, but then what?

That question triggered what I believe may be the answer: a new app coming out called Compass.

This is not some paid promotion. I am genuinely excited about this app and was introduced to it by the creator of Compass himself, Chris Dancy.

He spoke at the QS conference in San Francisco this summer and first established his overall philosophy to design with compassion. Dancy then presented Compass, the way to carry out his positive intention.

One key feature of the app, as it contrasts to Facebook up above, is that Compass shows us our memories in combination with a visualization of our data (see: above.) These photos may come with small reminders to keep us focused on a goal or even a behavior it automatically detects from us (see: the bottom left photo below.)

The result is Compass as a guide —  a friend — there to motivate us and help improve our wellness along the way.

I signed up as an Alpha tester soon after the conference and was able to experience the app first hand. Right off the bat, Compass was the most beautifully designed interface I have seen to date for a QS tracker.

You can view your entire day with a quick spin of the compass. You can view the breakdown your daily activities there, or in a timeline manner below. After a few days, Compass even began to predict my activities later in the day; for instance, an idea of what time I would be home for the night.

In my one month trial, I noted a few differences in my own personal behavior. I was exploring the Bay Area at the time and was even more alert to document my day with photos, specifically to see it in Compass. That spark alone is exciting enough to imagine the data it opens up (plus, I can be a nostalgic sap sometimes :))

It was clear that within days of getting settled with the app, Compass has the promise to be the one-stop app to track all things health, activity, wellness, and memories — and connect them all together.

For now, you can head over to existence.io to view more of the pretty display, understand the Compass philosophy even more, and sign up to be an Alpha tester yourself!

“Your behavior is the new device.” — Chris Dancy (@servicesphere) at the QS15 Conference, San Francisco


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Eating Any Time With More Energy

Continuing to look at my Daily Energy Curve, I wanted to understand how my meal schedule would impact my energy levels. I have been working on feeling as energetic as possible. I imagined the times I ate would contribute to that.

I thought I had detected a pattern when I ate a big breakfast I would feel warm and alert for several hours. And a big breakfast would account for all my calories until dinner. Would I crash in the afternoon if I had no lunch? Or if I ate a smaller breakfast would I crash mid-morning?

big breakfast

My Question

Did I have more energy through the course of the day if I ate one big breakfast and skipped lunch or if I divided my intake between a modest breakfast and modest lunch?

What I Did

I captured how alert I felt four times a day for 50 consecutive days during which I either ate a large breakfast and skipped lunch or ate modest breakfast and modest lunch. I then compared my alertness at different parts of the day during the two types of meal intake.

How I Did It

I set my alarm on my iPhone so it would alert me eight times a day. When the alarm went off, I used my DIY Tracker on my iPhone to capture how alert I felt.


The DIY Tracker captures a score of 1 – 5 on my alertness. After 50 days I took the data generated and eliminated days where I did not measure correctly or had food intake what was outside specific tolerances. This yielded 30 good readings. I separated the list into the two types of food intake and did a TTest comparing them.

What I Learned

There was no significant difference in energy levels through the course of they day based on whether I ate all at once or spread the intake over two periods. I compared the different intake schedules for each of four day parts and the average of the four. The TTests revealed that there was no difference between eating a single meal vs. splitting it into two.


Another personal story debunked. My body would process the nutrients on its own pace and as long as I was putting in the right amount by noon I was ok. Knowing this gives me a tremendous amount of latitude based on what is happening in my day.

I think about all the upsets around trying to eat on a rigid schedule in the morning and how much time I spent planning eating based on having to eat the “correct” amount. The answer is if I had enough calories and did not distract myself with hunger I would be ok.

If you want to try using your own DIY Tracker, you can download free instructions to get you started.







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Realizing 10K steps walking isn’t enough (for me)

Guys, I have to admit: this wasn’t a great week of exercise for me.

I was attached to my computer the first three days of this work week. I otherwise blamed a sore ankle and other family and friend commitments for not hitting the gym at night. It happens. But this week made me realize a change is in store.

I can’t be satisfied with walking 10K steps a day as a substitute for real cardio and think that I’ll maintain shape.

One metric that helps me conclude this: I gained 4 lbs in this week of general inactivity and none of my usual cardio. I thought I would be able to maintain, especially after a day where I literally went on a scavanger hunt through Chicago! There was a lot of walking amidst public transport, but I looked at the data afterwards and didn’t even arrive at 10K steps for the day.

84% of my total day's steps were from a scavanger hunt through Chicago. (Data via Moves)
84% of my total day’s steps were from a scavanger hunt through Chicago. (Data via Moves)

Do you ever feel that after a long 20/30 minute walk you got your workout for the day? That’s how I felt after my walk around Lincoln Park. Because I know the area so well, I can visualize the distance I covered and embellish it to be longer than it actually is. As you can see below, it’s only 1.4 miles.

My longest walk of the day — just 2K steps over 28 minutes.

Reflecting on this now, I remember feeling satisfied both during the above walk and after the scavanger hunt was done. My friend, and QS expert Mark Moschel, can attest: we went on the scavanger hunt together and I remember telling him “I feel kinda good, we got to walk around the city today.”

I was a little bit tired, but certainly would have had enough energy left for a workout after some rest. I didn’t push for it though because I thought for sure I walked over 10K steps already. As I’m finding out, I didn’t even reach that standard and even if I did, a few days a week of this amount of walking is not enough to substitute for little to no cardio.

Just today, in tracking my more typical work day, I arrived at the same conclusion. My longest walk so far has been 16 minutes, covering nearly a mile of downtown Chicago.

My longest walk so far today. Again, it looks longer and feels like more steps than it really is.

Since I’ve gotten settled back home after my trip this summer to San Francisco, I have arrived at the same takeaway I initially gathered out in the Bay. As I detailed here, I averaged about 7.5K steps a day for my trip, typically struggling to reach 10K with the mindset to walk more and explore the city. Likewise to this smaller sample size, I gained weight over 3 weeks given this activity combined with limited opportunities for cardio.


I hope by now you can take something out of my experience and apply it to yourself. But that’s the last point I want to make: for you.

I still have dreams of regaining my peak shape from my college years and still want to play basketball in competitive leagues for another few years going forward. For that type of athletic competition, I have to be in better shape, simple as that.

My conclusion is that 10K steps a day, though the standard healthy zone, isn’t enough. For instance though, 10K steps/day for my parents (in their 60s) is an amazing goal. That’s the beauty of what QuantXLaFont is setting out to achieve. Everyone is different and responds different to cardio, nutrition, sleep, you name it.


Up next: Give the DIY Tracker a free download and join me in tracking your own progress. For me, I intend on rating my physical activity and energy at the end of each day. I’m hoping the results will further drive home my conclusion and give me daily reminders that I’m still far away from my goal, whether walking or running. And with that… I’m going to hit the treadmill tonight!

Create your own QS tracker, which automatically records your resposnes in a Google spreadsheet, here.
Create your own QS tracker, which automatically records your resposnes in a Google spreadsheet, here.

BONUS: I also plan to use the data from my Chicago tourist scavanger hunt as part of a future follow-up with my past step count writeups: SF and at Lollapalooza. Stay tuned, looking forward to it!

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Daily Energy Curve: Blue Mondays

I’ve been enjoying debunking my own cherished stories about my Daily Energy Curve and I went after a good one about the restorative power of the weekend. I always thought that I had a fresh start each Monday after a weekend of rest. I thought each Monday I was like this guy, ready to get going and make it happen.



I was curious about this because I would assign work to either Friday or Monday based on how stressful I thought it would be. Given my story, I would move the tough stuff to Monday thinking I was more rested.

My Question

Was I more rested, awake and ready to go on Mondays vs. Fridays?

What I Did

I captured how alert I was and how much stress I was feeling eight times a day for 25 consecutive days. I then compared Monday to Friday’s in terms of mental alertness and stress.

How I Did It

I set my alarm so it would alert me eight times a day. When the alarm went off, I used my DIY Tracker on my iPhone.



The DIY Tracker captures a score of 1 – 5 on my alertness and stress level. After 25 days I took the data generated and cut it by Monday and Friday, doing a TTest comparing the two days.

What I Learned

I was no more mentally alert on Monday than I was on Friday. The TTest on Mental Alertness showed that there was no significant difference between Monday and Friday.


Awake Mental Alert Stress
Friday vs. Monday 0.10 0.50 0.04


Stress, however, was significantly higher on Monday than on Friday (p = .04). This made sense as I was moving tasks to Monday for no real reason other than my story about being rested. I have to conclude that I was overloading my Mondays as a result. What a lousy way to start my week.

Another story I had is that I was more alert in the morning than I was in the afternoon. I had even organized my day so that I would do my heavy lifting mental work in the mornings. Turns out that was wrong. Looking at the entire data set and comparing morning to afternoon, not a single measured dimension was significantly different.


Awake Mental Alert Stress
Morning vs. Afternoon 0.23 0.22 0.72


So combining the two, I think I was generating my own Blue Mondays by believing these two stories. I would try and shift all my hard work to Monday mornings, and the result was not better output, just more stress.

I will look to spread out the work more evenly and compare that to this baseline. At the very least, I will look to try and make Mondays less hectic.


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