4 Findings from 4 Days of Tracking: An HRV Case Study
Now comes the fun part. I wanted to share what I found after running a 4-day self-diagnostic experiment—I'd been itching to do something like this for a while. I want to keep the language simple so it's easy for anyone to follow.
Here are the 4 main takeaways (raw CSVs and technical notes linked at the bottom):
1. Smoking stresses my body, verified.
2. A high-calorie, high-fat meal takes around 4 hours to digest.
3. High (or very high) morning RMSSD isn't always better or a sign of recovery.
4. There is an extra recovery rebound post-workout.
1. Smoking stresses my body, verified.
Over the 4 days I tracked myself, this had the biggest impact by far—a habit I had kicked years ago and recently picked back up.
I realized that around 8 PM is when I usually smoke a couple of cigarettes. Plus, I measured right before smoking to catch the direct impact; across every reading, digestion was already finished and my system was relaxed with zero active stressors.
With cigarettes, my Stress Index spikes through the roof—doubling or even quadrupling:
• Oct 5: a +363% spike
• Oct 7: a +226% spike
• Oct 8: a +183% spike
By that hour of the night, nicotine leaves the body with a heavy burden to clear, making it much harder to ease into sleep.
2. A high-calorie, high-fat meal takes around 4 hours to digest.
This pattern was also easy to spot: the body starts reacting aggressively whenever a meal exceeds 700 kcal, especially meals packed with a solid amount of fat.
Using my data, I calculated my body's rule: every 100 calories knocks 170 points off my "rest mode" (which is why the blue trendline drops at a slope of -1.70).
A light 200 kcal snack barely moves the needle: the heart stays calm. But a heavy 1,000-calorie meal bills the body a tax of 1,700 points of calm, forcing it to work overtime until it gets back to baseline. In my case, these heavy meals took around ~4 hours on average to clear.
So my first clear conclusion from the data was that smoking and throwing a heavy dinner on top at that hour is a dumb mistake—it's like trying to put out a fire with gasoline. And this leads right into the next point.
3. High (or very high) morning RMSSD isn't always better or a sign of recovery.
Like clockwork, every morning I felt heavy like a tank, completely drained of energy and motivation, even though my first wake-up reading showed impressive numbers for RMSSD, HF, and Total Power. It had the textbook signature of peak recovery, but it completely clashed with how I actually felt.
My theory is that since a heavy meal takes 4 hours to clear, plus the cigarette effect, eating dinner at 11:30 PM meant my cardiovascular system was busy handling digestion until 4 AM instead of resting properly. Since I usually get up around 9 AM, I was robbing my body of half its actual recovery budget.
So when I put on the sensor right upon waking, it showed high recovery, but it was just inertia from delayed rest, accompanied by a feeling of heaviness and low drive.
4. There is an extra recovery rebound post-workout.
On the flip side, I also looked at what happens before the gym, after the gym, and right up until before the afternoon meal (~3 PM).
What I noticed here was a drop straight through the floor—the lowest of all measurements. It's even more aggressive than any meal or cigarette combined, which isn't necessarily bad; the body is designed to use this acute stress mechanism normally.
There is an average drop in HF (which indicates recovery: higher means more recovery) of -92% on average, taking roughly 2 to 2.5 hours to cross back over the baseline, and about 3 hours to hit what's known as the parasympathetic rebound, which surged nearly +200% above my general baseline.
In this case, I realized I didn't have true control measurements—just one rest day that behaved like pure recovery—to separate the effect of food from the gym itself, which will be great to test in my next experiment.
On October 8, I recorded my best streak: during that stretch, I felt sharp, motivated, had tons of patience to learn, and had enough dopamine to tackle things that demand full focus. It's a state that's hard to reach and one I want to see if I can replicate. So far, the only clear clue I have is that it was the day with the biggest parasympathetic rebound of the entire study.
Extra
Recently, I learned that room ventilation is crucial. I read that high CO2 concentrations in closed rooms can keep the body in an activated/sympathetic state and prevent optimal recovery. So starting October 5 (the CSV has a slight timestamp offset), I began sleeping with the window and door open. The fresh airflow was night and day compared to keeping everything sealed shut.
I'm not totally sure if it moved the needle—mostly because my nights were already hijacked by sympathetic stress—so I couldn't isolate the effect cleanly. But the goal moving forward is to dial in these variables so my brain can drop into low frequencies at night, which is my main area of interest.
Technical Notes
In the dataset, you'll find all the collected data in CSV format. This includes food logs, every measurement with its respective metrics, and the complete database exported from the sensor, including raw values and camera sensor data.
Regarding macro and micronutrient tracking: I have some experience with portion sizes and grams. While I didn't obsessively weigh every single ingredient with strict scale discipline, I did log every food item separately along with its exact timestamp.
I also included experimental tagging for my subjective state, though I haven't run any formal analysis on those tags just yet.
Data and code: github.com/LensHRV/n1-01-hrv
Conclusions
Given these findings, it's the perfect time to quit smoking—the impact is brutal and it's a completely dumb habit. I also need to cut back on late-night calories, or at least finish dinner 4 hours before bed. That's tough for me, but the goal is to get my numbers down to baseline before going to sleep.
For the next experiment, I'd like to give my body dedicated recovery time post-workout before eating light, and never stuff myself with meals over 1,000 calories. In my view, the human body just isn't designed to process that much food in one sitting.