I’ve tracked my daily routines for 90 days and this is what I’ve found

Gabrielė Jusaitytė
Jan 28 · 10 min read

Having my gallbladder removed at the age of 14, dozens of allergies and an increased heart rate makes you wonder. At the age of 27, I’m living with pretty much constant bloating, my heart rate reaches 150bpm after a few flights of stairs and frequent headaches are starting to irritate.

I’ve seen gastroenterologist, allergologist, a cardiologist and gynecologist and except for a proven hay-fever and a slight reaction to apples and chicken — I’m supposed to be perfectly healthy.

Even if you can’t relate to the listed health issues, I believe I’m not the only one looking to answer questions like — what food ingredients make me feel bloated, does skipping a meal cause a headache and how many hours of sleep I need to be most productive?


App stores seem to be filled with food and sleep trackers, self-care and meditations apps, tools for forming good habits and breaking bad ones and apps for tracking and actually doing the workouts. I definitely haven’t checked them all, but the pattern was clear — you can track pretty much everything, but the data is not actionable.

For example — what does a heart rate of 96 actually mean? Nothing until you can correlate it with something that matters to you.

To get the full scope — there’s usually a mix of heart rate, sleep duration, food intake, etc. coming together to answer questions like these. So why do I sometimes feel the way that I feel and what can I do to change it?

How tracking is turned into insights:

Feelsom app allows entering information without having to type a single line, therefore all of the possible options are presented as predefined answers. The way the calculations are done is firstly by attributing value to the answers depending on both — scientific research (hours of sleep) & common sense (productivity).

I’m currently experimenting with the interconnectedness of:

  • Sleep
  • Food
  • Mood
  • Productivity
  • Health
  • Physical Activity

All of the inputs have their own measurement value: the better the input — the higher the value. For instance — If you’re logging your productivity, the answer ‘Hell yeah’ would have a value of 5 and ‘Not at all’ — a value of 1. Having logged the former values — the average productivity would be counted like : (5 + 1)\ 2 = 3 (when ‘2’ stands for an overall number of inputs).

To compare two different categories and show the relation between them, we need to see how one variable changes when another one is introduced into calculation. So how productivity depends on a specific type of physical activity? In this case, the results would be formed by counting all the logged productivity values and applying a ‘filter’ of a specific type of physical activity that was logged on the same part of the day. So the average productivity would be counted only on the days that specific activity was logged. The chart, in this case, would provide a visualization of the calculation by comparing the averages of productivity filtered by different activities between one another.

The way I track my well-being is by logging my inputs to Feelsom 3 times per day to cover the changes in my mood, productivity, and health during the day and adding information about my food choices for breakfast, lunch, and dinner. For additional data, I’m tracking my heart rate, step count and advanced sleep stats with Garmin watch (Forerunner 645).

What is really true is that your well-being is very personal and some things that could sound even counterintuitive could actually work for you.

I’ll continue on listing my top findings, though you might ask, why some random person’s insights should interest you? I would suggest thinking about this — there is an overwhelming amount of data suggesting what is good for you, and we all have a lot of presumptions, but what is really true is that your well-being is very personal and some things that could sound even counterintuitive could actually work for you.

What I learned:


A lot of my concerns and symptoms are related to nutrition and tracking every food intake together with the feeling afterward is not quite enough. It’s extremely difficult to use the practice of removing a suspected ingredient from your diet, when you suspect almost everything and when you usually eat a lot of different ingredients at once.

A way to solve this is by trying to search for significant correlations between a food ingredient and bloating. The bars in the graph below are being formed by ranking food ingredients that were logged on the same part of the day when bloating was experienced. The aim is to find specific ingredients that might have an impact on the chosen variable (in this case — bloating). For example — the bar that represents ‘Potato chips’ and has a value of 100%, means that 100% of the times when ‘Potato chips’ were logged as a food ingredient — bloating was experienced.

And just like that, your doubts and suspicions are being backed up with calculations. This ‘cheat sheet’ makes it a lot easier to experiment with my diet. I’m still adding my gut feeling into consideration, because first — correlation doesn’t always mean causation and when unusual ingredient (for example — I don’t usually eat turkey) ends up on my plate — a high percentage could be only a coincidence.

It is clear though, with every input my list gets more clear — random ingredients are starting to disappear and the real trouble makers are being raised to the surface.

But what about feeling bloated when you feel like you haven’t even eaten anything? What caught my attention is that I’m logging bloating more frequent after feeling ‘light as a feather’ after a meal, than when I’m feeling ‘‘So full can’t breathe’ — it might indicate, that I need to rethink my snacking habits and very ‘light’ lunch choices as they don’t do any favors for me.

The bar that represents ‘Light as a feather’ and has a value of 80% means that 80% of the times when ‘Light as a feather’ was selected as an answer of feeling after a meal — bloating was experienced afterward. These bars are formed by ranking inputs of feeling after a meal that were logged on the part of the day when bloating was experienced.

Feelsom: Bloating & Feeling after a meal


8 hours of sleep are optimal in terms of feeling after sleep. You’re probably thinking ‘No sh*t Sherlock’ as it is widely agreed that a healthy adult needs 7 to 9 hours of sleep, but at the end of the day the most important thing is — when you wake up — do you feel fresh and full of energy or already tired? So in my situation — any recommendations to sleep for at least 7 hours is not an option. It’s 8+

Fatigue has the strongest impact on my sleep quality. Logging fatigue as a health symptom, the evening before, might have a negative impact on my sleep quality. So if being exhausted leads to poor sleep quality, it can easily create a loop. A nap might be in order.

Feelsom: Sleep quality by Health symptoms

Sleep latency is way shorter when I’m very productive. It seems that when I’m logging ‘Hell yeah!’ as productivity value the evening before, I’m falling asleep faster. This sounds a bit counterintuitive as it is widely recommended to ‘wind down’ before going to sleep. Though what interests me, is that it takes twice as long to fall asleep when I’m ‘Kind of’ productive — does it mean that in the first case my energy levels are exhausted and in the second — my brain stays active for longer? This needs further investigation.

Feelsom: Sleep latency by Productivity


Have you wondered how mood depends on sleep duration? In the chart below, the results are formed by counting all the logged mood values and applying a ‘filter’ of a specific sleep duration that was logged on the same day. For example — counting mood values of the part of the day when ‘Definitely 8 hours!’ was logged for sleep duration.

The line above marks an optimal value of overall mood inputs. If a bar is higher than the line — that length of sleep might have a positive impact on your mood & if it’s lower than the line — a negative one. When a bar is in line with the optimal line —the input has no significant impact on mood.

Looking at the chart, it’s quite clear that 9 hours of sleep might impact my mood in the best way. 7 hours though, stands out again — my mood is way below average after logging 7 hours of sleep, which coincides with a worse feeling upon waking up as well. So once again, 8 hours of sleep, for me, are necessary to keep those #positivevibes.

Feelsom: Mood by Sleep Duration

Physical activity or lack of it doesn’t have any significant impact on my mood. though if digging deeper into exercise types — walking does stand out — long walk works like mood booster for me!


I am most productive on Tuesdays and least productive (of course) on the weekends. An interesting insight could be that my productivity on working days is usually above average, though drops on Thursday! I would probably thrive in a 4 day work week.

ALERT! Sleeping less than usual seems to have a strong connection with a decrease in mood, though this is not the case with productivity — the less I sleep the more productive I am! This could be connected with some harsh deadlines and working long hours, though in this case, there wouldn’t be a sudden drop in productivity when sleeping 8 hours or more.

Feelsom: Productivity by Sleep duration

Food & productivity: this is just awesome! The top 10 ingredients that might be correlating with an increase in my productivity, contains mainly vegetables, few fruit options, pumpkin seeds, and salmon. My brain just loves healthy (and fatty) foods!

Closing remarks & why you should consider tracking your daily routines

I’ve shared my experience and findings when tracking my daily habits for 90 days. Looking at the results, I’ve already learned loads of things about myself and my body. For example, I learned that my favorite smoothie triggers bloating. My mood decreases in the evening and working out doesn’t seem to boost it. I’ve learned that poor sleep quality has a strong connection with my digestive system and that to feel good after physical activity I need to get at least 8 hours of sleep.

I’ve also learned a level of detail for each individual category, including:

  • I’m most productive when — getting 5 -7 hours of sleep, eating veggie based meals, feeling stressed (!?) and doing some exercise.
  • To feel good health wise — 7- 9 hours of sleep (7h having the biggest impact), doing some stretching and definitely avoiding turkey, tuna and potato chips.
  • For the best sleep quality (from falling asleep to waking up fresh as a cucumber) — not being productive and staying positive (probably just sit on the couch watching Netflix) the evening before, avoiding turkey and tuna once again and getting 9 -10 hours of sleep.
  • For a better mood I need — a long walk, getting 8–9 hours of sleep, some comfort food and nuts (!)
  • To make the most out of physical activity — getting 9 hours of sleep, avoiding cabbage, garlic and beans and doing Pilates, because it gives an energy boost!

But the biggest thing I’ve taken away from doing this is that I’m finally able to confirm my hypothesis, back up my doubts with evidence and most importantly — solve problems.

I know what makes me feel better, how to adjust my diet and how to improve my productivity. Just by tracking my routines I’ve made myself a ‘cheat-sheet’ of how to live my life.

Just by tracking my routines I’ve made myself a ‘cheat-sheet’ of how to live my life.

For full disclosure — Feelsom is founded and bootstrapped by me, a real person with real problems, and if you want to try it by yourself the app is available on the Apple App Store. Analytics feature includes a 7-day free trial, though daily, weekly and monthly reports are available for free.

So whether you’re just curious about your well-being, looking for the perfect formula to feel better, be more productive or live a healthier life — as cheesy as it may sound — tracking small daily activities can make a difference.

Download it here and let me know what you think!

Gabrielė Jusaitytė

Written by

A freshly baked founder, on a mission, to build a digital health startup.

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