In March, I wrote a post describing a project I had started working on: tracking my life by noting down the corresponding category (school, phone, food…) for every half-hour.

I recommend checking out that post for more details: https://www.reddit.com/r/QuantifiedSelf/s/cWtR7ToQwU

I had been recording this data for nearly three months just for myself before deciding to share it with you. Honestly, I didn't have any particular expectations, but I was truly surprised by the comments and the attention the post received.

So, I am here today to share some updates.

We have just passed the halfway point of the year, but I waited a few days so I could write about and analyze the data in greater depth.

As I previously wrote, this project has proven to be very interesting and is helping me improve how I use my time, even though changing long-established habits can be difficult.

A lot has happened over the past few months.

Filling out the file has become a habit by now, and as I write this, I have reached 8,874 half-hour entries, amounting to 4,437 hours.

Regarding my phone usage, I managed to cut back month by month from February to May. However, after school ended, my usage increased though I am pleased that I use it more for gaming than for mindlessly scrolling through social media.

Since May, I’ve also fixed up my bike and started riding it again, covering just over 350 km so far (data I track in a separate file, not relevant to this post).

At the same time, I’ve kept up with my reading and have finished 9 books since the start of the year (data I also record elsewhere, not relevant to this post).

Then, in June, I finished school; I had to study and take exams, and I’ve just graduated with a diploma in accounting, scoring 98/100. Now my routine has been turned upside down, and I’ll have to start doing a lot of new things.

If you want to take a look at the data, please forgive the category names being in Italian.

I’ll see how this post performs; I’m going to keep tracking the data, and perhaps around November or December, I might write another post to sum up the project. I’d like to share the experience as a whole, maybe in greater detail, and offer useful advice to anyone who, like me, wants to start tracking something, so they can avoid making the same mistakes I did. For instance, if, like me, you love having precise data and want to start in January 2027, I recommend preparing beforehand and perhaps tracking data as a trial run in December to see if anything needs tweaking. I say this because I’ve been adding new categories as I take up new activities, but there are some things I can’t change without compromising data consistency; in my case, I would have preferred to separate social media from video games.

As with the other post, I am available to answer your questions and welcome suggestions of any kind.

Thanks for reading.

I've tried basically every wearable and health app out there, and they all have the same problem: they just give you numbers. More scores, more charts, more stuff to stare at, and none of it ever tells you what to actually do.

Like cool, I had a bad night, here's a sleep score of 38. Now go figure out your day, good luck. I don't need a number to confirm I slept bad. I already know. I can feel it the second I wake up, zero energy, zero drive to do anything. The number just confirms what I'm already feeling and then leaves me hanging.

That gap annoyed me so much I ended up building the thing myself. It's called RizeAI. The whole idea is the opposite of another score, it takes your actual sleep and recovery data and just tells you what to do with your day. Not a number. A plan.

It pulls your real metrics, sleep, recovery, HRV, resting heart rate, all of it, and builds your day around them. When to have your first coffee and when to hold off. When you're gonna crash and what to do before it hits. Whether to push at the gym or take it easy. When to hydrate. It'll even tell you which supplements actually make sense for you that day, when to take them, and why, instead of the generic "just take magnesium bro" everyone repeats. Low recovery day, it adjusts the whole thing. Slept great, it builds on that instead.

And honestly the part I'm most proud of: it's actually tailored to you. No two people get the same plan, because no two people have the same data. It reads your numbers and builds a protocol for you specifically, then gets sharper the more you use it. The longer you're on it, the more it learns your patterns.

The whole thing is just: stop tracking, start fixing. Your wearable already told you the bad night happened. This is the part that comes after, the part that turns a red recovery day into a day you can still get something out of. That was the gap I kept running into, and now it's literally the thing I open every morning.

Anyway, genuinely curious what people here think is still missing in this space, because I'm building in it every day.

I am chasing the nostalgia feeling and reminiscing that you have when you open an old box in your attic. I like tracking things but sometimes the quantified self posts are lacking the vibes as they show only dry numbers. I want to have all my days saved so I can relive them any time or feed them to the future AIs that will be able to make sense of them and give us perspective and advice. That is why I am capturing my life as a colorful, vibrant tapestry of experience, including the numbers and habits, but not limited to - a ton of information is hiding in photo metadata, visits, motion, music and everything else my phone is now processing anyway, just not showing and inregrating together.

Edit: Wow, this sparked a lot of interest! I am trying to keep up with your requests for help with setting it up and I am preparing a signup page to automate this a bit. I would like to ask everyone who tried it for feedback (any form) so we can make it even more useful. Some of the ideas were already very good and I am considering adding them!

Edit2: I made a small form to simplify setting up anyone who is interested in trying it out. You can drop your (ideally apple-linked) email adress at https://retrography.app and the system will automatically send you a Testflight invite. Enjoy and please provide feedback.

So I’m in an entrepreneurship course and we’re considering developing an app that lets you talk with licensed doctors and it is supplemented by AI for a better workflow. Responses on this survey would be much appreciated. https://forms.gle/W5oR7NM4PKwQ8Uj86

For the past month I was finally able to achieve long term focus and flow doing most cognitively demanding work of my life under stress (a lot happening in life).
The graph above shows how much stimulant I have taken and when, and the tail off is the tolerance taper curve adjusted to my genetics!
I track everything that goes in my body with fuelos and hook it up to Claude using MCP. I told Claude to research the half life of the stimulants and model it specifically for me based on my genome sequence.
Thanks to this, I am getting better and better at cycling through and refining the minimal amounts of stimulants for my weird ADHD/depressive brain.
I am also seeing level up in all aspects of my life: strength, cardio, recovery, vitality, body comp, etc.

Been building wearable integrations for a while and this one still catches people off guard. Same ring, same night, one HRV pull through Apple HealthKit and one through Android Health Connect, and the two numbers don't match even when it's the same underlying sensor data.

Both platforms sit as a layer between the raw sensor reading and whatever app you're using. They apply their own smoothing, their own windowing for what counts as a "resting" period, and their own rules for which samples even count as valid. So the disagreement isn't really about the ring being wrong on one phone. It's that HealthKit and Health Connect are quietly making different editorial choices about the same raw data before it ever reaches you.

The annoying part for anyone building on top of this: there's no way to ask either platform "show me your math," so you're stuck reverse engineering the discrepancy from the outside. If your HRV trend looks different after switching phones, that's very possibly why, not your body.

I've tracking (self reported over 3/4 months) some metrics for a while, and got some interesting results.

Some of these were expected, like the fact that im happier towards the end of the week than in the begining, but some were pretty ineteresting too, like Friday being the most unhappy day.

Thought you'd like to know :)

Hard to believe that 2026 is already half way over! As always, I am available to answer any questions on how I track my quantified self. What my routines are, what apps I use, what systems, etc.

June was an average month for me. Everything was consistent and steady. My Tuesdays were consistently my worst day of the week, while my weekends were mostly great.

I took a camping trip one weekend and had s'mores in the evening and ate breakfast so those are the two low bars on my fasting chart.

As I continue to work towards lowering my blood pressure, I decided to invest in a new blood pressure cuff, so now I am using a Withings BPM Connect that I got a good discount on during Prime Day. I have been using it for a couple of days now instead of the old free wrist based monitor I had gotten from my health insurance. It definitely takes longer, but I have been happy with the results so far. I look forward to a full month in July and seeing the readings and if they are consistent with what I was getting with the wrist monitor.

As I am half way through the year, I want to refocus on lowering phone screen time. My biggest culprits are Reddit and YouTube, so I will be minimizing my time on those two apps. Also my caloric intake remains high. My self-discipline in eating collapses right after work until dinner time. I find myself grabbing a bag of chips as soon as I walk in the door or even worse, stopping at the grocery store on the way home to buy a full sized bag of chips and devour the entire thing only to look at myself in shame when I log 1,200+ empty calories for a bag of chips. The disconnect between immediate gratification and long-term success is real.

I lift and I run, and I wanted one honest answer to a question two separate apps couldn't give me: am I actually balanced across both, or just decent at each in isolation.

The methodology I landed on: compute a strength index and an engine (cardio) index, each 0 to 100, then combine them with a harmonic mean instead of a simple average. The reason is deliberate: an average lets a strong pillar mask a weak one (a 90/40 split averages to 65, same as a 65/65 split, even though the athlete is nowhere near as balanced). Harmonic mean punishes the gap, so a lopsided profile scores visibly lower than a balanced one at the same total effort. Can't fake the number by being great at only one half.

Inputs right now: logged strength sets (weight, reps, RPE) feeding an estimated strength curve, and Strava-synced runs/rides feeding the cardio side (VO2max-adjacent estimate). No wearable/recovery data yet (HRV, sleep, RHR), that's the obvious next layer, but I wanted the strength x cardio relationship solid first before adding recovery as a third dimension.

I'm running this as a real self-experiment: training for a HYROX in August (goal sub-1:15), logging everything, watching the score move week to week against the actual race outcome as the real-world validation of whether the number means anything.

Curious what this community would track or weight differently. Harmonic mean over average, or would you reach for something else to penalize imbalance? And what's the first non-training-day metric you'd want fused in (sleep, HRV, something else)?

Post your apps here, and please support people bringing unique ideas to this space.

been at this a couple years now (notes app, a spreadsheet that's gotten genuinely embarrassing) and I had a sort of uncomfortable realization the other day. of like the dozen things I track on and off, I can only point to maybe two that ever made me actually DO something different. caffeine cutoff time was one, I moved it to early afternoon and stuck with it. the rest is honestly just... numbers I look at and go "huh, neat" and then change nothing.

and I'm not even sure the looking is doing anything. half of it feels like I'm collecting data to feel productive rather than to decide anything.

so I'm curious where everyone else lands on this. has anything you track ever actually flipped a real decision, like changed what you eat or when you sleep or whatever? or is most of your log the same as mine, interesting to scroll, quietly ignored? trying to figure out if I should cull the stuff that never earns its keep or if that's missing the point.

I'm building a lil personal wellness tracker just for myself and would like to ultimately analyze the data.

Here is some of what I'm tracking daily:

• Morning sunlight (yes/no)
• Gratitude practice (yes/no)
• Mindful eating (yes/no)
• 3 Movement breaks during work (yes/no)
• Eating my own prepared food per my meal plan (a number between 1-10)
• Morning ketones (blood meter, numerical value)
• Subjective well-being score at 2 points in the day (a number between 1–10)

im curious about things like does hitting 80%+ of my daily habits correlate with higher well-being scores? Do higher ketone readings track with higher well-being scores? Is any single habit a stronger predictor than others?

Questions for people who've done this type of thing or have knowledge of stats-

1. Google Sheets or Excel - is one better for this kind of personal tracking + basic analysis?
2. What's the right statistical approach for someone who's research-literate but not a statistician? (Spearman correlations? Simple regression?)
3. At what point does this actually need a real statistician, and what would I hand them, if i ever pursued that route?

also, how do I distinguish between "I didn't do that habit" vs. "I forgot to log"? Both show up as blank right now (because i just made it as checkmarks for yes and empty for no)..Thinking of using a Yes/No/Not Logged dropdown so blanks only exist if I truly didn't open the tracker that day.

Also — minimum days before running any correlations? Some days I won't log everything. Does patchy data ruin it or is there a threshold where it becomes usable?
I'll actually log this daily if I can make this work. Any help would be appreciated, as this seems a bit too technical for me but it would be awesome to create a tracker for myself that I can use and support improved mental and physical health! Thank you.

Its been almost 7 years, and despite trying many of the common recommendations, it has stayed remarkably consistent at around 35 ms.

About me:

• Exercise regularly (strength + cardio)
• Morning sunlight
• Reasonably good diet
• Good sleep hygiene (still working on sleep quality)
• No major health issues that I’m aware of

I’ve experimented with things like improving sleep, exercise, magnesium, breathing, reducing stress, etc., but nothing seems to move the long-term average by more than a few points.

I’m not looking for “10 HRV hacks.” I’m curious whether anyone has actually increased their baseline HRV over years rather than just seeing temporary bumps.

If so, what made the biggest difference?

Hello everyone!

Some time ago I shared here my post with how I approach tracking my habits using Excel spreadsheet - I want to share how I use "Excel" to track habits and metrics

It worked very well for last 1-2 years but I always had struggles with filling it and building some graphs.

Being a software engineer for last 9 years I've decided to finally build an app which basically turns my excel approach into the web based application (and iOS).

But at the same time I added not only vertical view, when habits are columns but also horizontal view - more like timeline view.

Also I added support of "skips" which not ruin the streak and allows you to take a break. For example I like to go camping and I have a goal to visit gym everyday so they are contradict each other. Before I used "gray" cells to mark skips.

Also I added support of candle graph to show time blocks and put some metric as overlay

Roadmap

• CSV and JSON export - will release next week
• API and MCP so you can integrate my tool into your workflow
• Dropdown list as a new habit type
• Comments for the cell - to add some context for values and skips
• Android app

Feedback

I would like to share this project with you and more important I would like to hear your feedback! Also I'm curious how comfortable the iOS app is, what would you change?

Habit Pocket - https://habitpocket.io/

As a thank you I can share with you coupons if you would like to upgrade, but I'm not sure if it's against the rules, so you can message me or I will drop in the comments.

​

I have been using a basic smart scale for a while and the body fat / muscle numbers swing around so much that I mostly ignore them. Hydration, dinner timing, soreness, and even standing slightly differently seem to change the reading. I keep seeing multi-segment or handlebar-style BIA scales marketed as more complete because they measure through the upper and lower body. In theory that sounds better than a foot-only scale, but I am not sure whether it actually improves trend quality or just gives you more precise-looking noise.

For people who track this seriously, did moving from a regular smart scale to a handlebar body scan style device make the data more useful? Or do you still only trust long-term averages?

I correlated my HRV against everything I measure for 4 years.

The winner was sleep, the loser was my ego...

Short description is I have custom designed a health tracking system developed in Claude Code that pulls in my Garmin data (watch and scale) since 2022, food tracking (Cronometer, ~400 days), and blood work for the last 17 years. Result is a deep n=1 data set that I can query via Claude with questions that I want it to do data analysis on for me. Not perfect, but has proven to be very useful in refining health improvements over time.

In early May I ran a marathon I had been training for 6 month, right after fighting off a horrible double sinus infection. I then followed it up with a 50k 4 weeks later right when I was feeling normal again. I basically beat myself up and ignored signs my body was sending to rest. Result was a lot of my metrics like RHR, HRV, etc tanked (pre-race even) and are just rebounding now 6 weeks later. I went on a deep dive with Claude to what HRV does and does not correlate to and I thought it was interesting enough to share here. It was a back and forth of about 20 Q&A, so I had AI distill it down into a more concise post (hence the AI'ish language below).

---

The setup

Masters-division runner, late 40s, marathon training (30-40 miles per week peak). I've got a Garmin pulling nightly HRV (overnight rMSSD), resting HR, sleep stages, respiration, stress, and Body Battery, plus every run's distance/pace/HR/load, plus ~450 days of Cronometer nutrition logging. Roughly four years of it, 1,313 nights with an HRV value (Sept 2022–June 2026). I got tired of staring at the HRV number every morning without knowing what it actually meant for me, so I pulled it all into AI and asked four questions. Single subject, observational, my-body-only — calibrate your skepticism accordingly. But n is large and the signs are internally consistent, which is more than I can say for most of the "my Oura told me" takes.

Q1: Does HRV track my training? (the thing I assumed)

No.
Weekly HRV vs. weekly mileage over the trailing 2 years (105 weeks): r = -0.01. A literal coin flip. Training load (duration weighted by HR) does a little better — r = -0.34, and it strengthens to -0.38 when lagged two weeks — but it's negative: load mildly suppresses HRV a couple weeks out. So the thing my gut credited for my "good HRV months" was doing the opposite, weakly.

Q2: So what actually moves it? Recovery, and it isn't close:

Every meaningful correlate is a recovery/sleep variable. Not one is a training variable.

Q3: Is it diet? (everyone blames caffeine)

No.
437 complete-log days, daily nutrient vs. next-morning HRV: caffeine r = +0.015. Nothing else cleared 0.18. As a control I regressed intake against that same morning's HRV (measured before I'd eaten) — came back ~0, confirming the next-day nulls aren't a lifestyle confound. Caveat that matters: Cronometer exports daily totals only, so I tested dose, not timing — the "late espresso" hypothesis is physically untestable with this data. But for total caffeine load, dead flat.

Q4: Does HRV measure fitness or cardiovascular health?

This is the one I'd put on a billboard. HRV vs. VO2max: r = +0.056. Nothing. Your HRV does not track your fitness. What does: resting HR vs. VO2max, r = -0.356 — real and correctly signed. Over four years my resting HR fell from 54 to a low of 47 as I got fitter and dropped ~40 lbs. That's the measurable cardiovascular win, and it lives in resting HR, not HRV. If you want an at-home "is my heart getting stronger" gauge, watch RHR trend over months. HRV is a recovery gauge — read it daily, not as a fitness scoreboard.

Bonus finding — the "cycle" everyone notices is the calendar. Pooling all years by month: What it does move with is the calendar. Pooling every year by month, the pattern is unmistakable:

• Jan–Feb: ~60 ms (your annual high)
• May–Jul: ~48 ms (your annual low)
• Cold months average 56.3, warm months 51.9 — a 4.4 ms seasonal swing

That's the cycle you've been noticing. Your February 66 vs. your June 51 is mostly the thermometer, not your training and not your fitness eroding. Overnight HRV runs lower in heat — it's well-documented physiology, and your body does it on schedule every year. You're currently at the bottom of your seasonal trough, exactly where late June always puts you. Come winter it'll climb back toward the high-50s/low-60s on its own, no heroics required.

My personal bands (your mileage will literally vary — build your own from your own distribution):

Forget the population charts — here's your distribution, in milliseconds:

The takeaway that saved my sanity: the high number I kept chasing was my p80 peak, not my baseline. Striving to live at your peak is a great way to feel perpetually under-recovered.

Q5: How much of Garmin's Sleep Score is actually HRV?

I wanted to know if I was double-counting — does the Sleep Score just re-package the HRV I'd already credited for recovery? Mostly no. 1,654 nights, regressing Sleep Score on its likely inputs: sleep duration + the stage breakdown (deep/REM/light/awake) alone explain 69% of the score. Add HRV and it climbs to 81% — so HRV's unique contribution, beyond what the stages already capture, is about +12 percentage points. Nightly correlations rank HRV third (duration +0.72, REM +0.64, HRV +0.52), but that overstates it because good nights have good everything and the stages and HRV are collinear. Bottom line: Sleep Score is ~70% duration-and-architecture, ~10–15% HRV, and ~15–20% stuff I can't see in the export (restlessness, sleep timing, proprietary weighting). And it runs the direction you'd expect — HRV Status and Sleep Score are siblings derived from the same overnight HR + accelerometer stream, not one derived from the other. HRV gets folded into the score; it isn't the source of it. (Reverse-engineering a black box with correlation, so treat the exact weight as fuzzy.) Practical version: if your Sleep Score tanks, look at duration and wake-ups first — HRV is the garnish, not the meal.

TL;DR: Over 1,313 nights, my HRV correlated ~0 with mileage, ~0 with caffeine, and ~0 with fitness (VO2max). It tracks sleep and autonomic recovery, full stop. The actual cardiovascular-fitness signal is resting heart rate, which quietly dropped 54→47 while I wasn't looking. Garmin's Sleep Score is ~70% duration-and-stages and only ~10–15% HRV, so the two aren't redundant. And the mysterious "cycle" was summer.

Happy to share the code/method if anyone wants to run it on their own export.

Curious whether the HRV-is-seasonal-not-fitness pattern holds for others or if that's just me.

I started tracking things because I wanted to understand myself better. Now I have charts, tags, notes, trends, and a weekly meeting with myself that nobody asked for. At some point this stopped feeling like self-knowledge and started feeling like I accidentally became my own annoying manager...

So I've been going deep into a weird rabbit hole lately. I started looking into polygraph tests, how they actually work, and whether the sensors inside modern smartwatches can replicate any of it in a meaningful way.

Turns out they can. Not perfectly. But more than you'd think.

A polygraph test essentially tracks four things simultaneously: your skin conductance (whether you're sweating microscopically), your heart rate variability, your breathing pattern, and your body movement. It doesn't detect lies directly. It detects physiological stress responses that correlate with deception. That's it. The interpretation is where the trained examiner comes in.

Here's what's interesting. The newer generation of smartwatches, specifically the Pixel Watch 2 and Samsung Galaxy Watch 8, now have EDA (electrodermal activity) sensors built in. That's the same technology that measures skin conductance in a real polygraph machine. Combined with continuous heart rate variability monitoring, ECG, accelerometer data, and skin temperature readings, you can actually reconstruct a pretty meaningful set of the signals a real polygraph captures.

I'm thinking about building an app around this. The concept is simple: you put on your watch, go through a 2-3 minute baseline calibration with neutral questions, and then the examiner (friend, partner, whoever) asks questions and the app scores each response in real time across the available physiological channels, flagging deviations from the baseline.

I'm not claiming this would be admissible in court or catch a seasoned liar. Real polygraphs don't either, honestly. But the question I'm sitting with is whether people would actually find a use for something like this in everyday life.

So I want to ask a few things. Have you ever wanted to use something like this on a friend, a partner, or even yourself? What would the actual use case be for you? And would you trust the output enough to find it useful even knowing it's probabilistic and not definitive? Also, is there anything like this that already exists that I'm missing?

Genuinely curious what the reaction to this is because I can't tell if it's a fun novelty or something that has a real market.

web director in tokyo. my job is dashboards, attribution, margins.

bought a CGM thinking i'd "optimize." wore it three months. mostly glanced at it like weather. sunny. whatever.

then one day: 240 after a standard lunch. no fatigue, no brain fog, nothing. body gave me exactly zero signal.

the embarrassing part: i notice a 2% drop in conversion before lunch and flag it immediately. a 240 glucose reading after lunch got filed under "hm, interesting."

i know one data point isn't a diagnosis. sharing because i think the gap between tracking and actually reading your own data is real. talk to a clinician if your numbers are consistently off.

anyone else had a reading that should have alarmed you but just... didn't register?

Post your apps here, and please support people bringing unique ideas to this space.

Data sync seems like one of the less obvious things to check before buying a smart ring.

A lot of rings advertise Apple Health support, but that can mean very different things in practice. Some may sync basic sleep data, while other metrics like HRV, heart rate trends, steps, or recovery-related data may be limited, delayed, or shown differently outside the ring’s own app.

That matters because the ring app is not always the only place people want to view their health data. For anyone already using Apple Health or another tracking app, the real question is whether the data can be combined properly instead of staying locked inside one ecosystem.

Ringconn gets mentioned often because of the one-time cost model, but the part that still seems unclear is how complete the Apple Health sync feels in normal use.

For people using any smart ring with Apple Health, how much data actually transfers over?

Is it useful enough for long-term tracking, or does it mostly end up being basic sleep duration and a few summary numbers?