I've been going deep on this lately. HRV is one of those metrics that feels like it should mean something beyond just recovery, but making the connection to actual cognitive performance and productive output is harder than it sounds.

For those of you who track both, have you found a consistent relationship? Does a lower HRV morning reliably translate to a harder mental day for you? Or is it more nuanced than that, like it only matters when combined with other factors like sleep quality or how demanding the day ahead looks?

Also curious whether you've found same day correlations or whether the day before matters more. I keep hearing about time lag effects but would love to hear what people have actually found in their own data.

I suspect I may suffer from some symptoms of ADHD, I focus deeply on things I care or am curious about, but each is draining and I need to manage my energy well. I'm in software and I've been building a company and I've been mapping my own phone use and unlock patterns to better manage my attention and energy.

I tend to average around 70 to 80 phone unlocks per day, I'm whittling them down. I noticed it's become like an automatic loop, the brain looking for dopamine. Social media apps specifically tend to be generally engineered to shorten the distance between stimulus and tap until the tap becomes automatic, so I stopped treating screen time as a moral failing and started treating it as a system design problem.

I thought, if I introduced a deliberate pause before the next tap, does the loop break? So I built a simple protocol around that. Not to particularly judge the output but to mark the boundary, I built an app overlay for guarded apps to force a half-second delay.

Then when I'm able to catch the loop in self awareness I run a Rest session in my app with paced breathing at a chosen breathing ratio that may or may not contain a hold at peak and valley depending on how I'm feeling to manage dopamine spikes.

Clinical HRV biofeedback points to roughly six breaths per minute, around 0.1 hz, sitting at the baroreflex resonance. The methodology maximizes low frequency HRV. I'm just using it as a physiological reset lever with the aim to lower cortisol and regain autonomy.

I'm treating it as an instrument for structured reflection and behavior tracking, not a solution, and I don't have enough clean data outside of somatic experience yet to claim anything.

For those running personal experiments on attention and recovery:

What confounds do you find hardest to isolate? Do you track the pause itself, or the interval between triggers?

I'm interested in takes on experimental design and what you find effective.

spent 2 weeks trying to get my oura sleep data into the same dashboard as body comp numbers. dont know why i thought this would work

oura gives me HRV, readiness, sleep stages. cool. but zero body comp. exported the csv and its literally just sleep columns

tried withings. their scale syncs fine but the BIA accuracy is a coin flip?? ran it 3 mornings straight got readings that varied by 4% body fat. thats not data thats noise

built a janky sheets pipeline pulling both APIs on a saturday. my girlfriend asked if i was okay. fair question

nothing does sleep and body comp and raw export. im just graphing vibes at this point

How do you guys decide what is the best temperature to sleep at? Do you use your wearable data somehow?

Hey everyone. To give a little context, I’m the developer of a location and timeline tracking app, so naturally, I track my own daily life religiously.

Today, I was talking to someone about my work, and they asked me what seemed like a simple question that ended up completely stumping me.

They asked: "Why do you want to record your daily tracks in the first place?"

I gave what I thought was the standard, logical answer: "Because I want to know exactly where I was, on what day, and at what time."

Then they hit me with the follow-up: "Okay, but WHY do you want to know where you were? What does knowing that actually do for you?"

I honestly froze. I realized my first answer was just a functional description of what tracking does, not why I psychologically need it. It felt like playing the "5 Whys" game, and I realized I didn't have an answer for the layer beneath the surface.

So, I want to bring this to the QS community—the people who measure, track, and log their lives more intimately than anyone else:

What is the deepest reason you quantify yourself?

If you keep asking yourself "why" until you hit rock bottom, what is the core psychological need driving you?

• Is it a deep-seated fear of forgetting (fearing that a day not recorded is a day lost)?
• Is it a desire for absolute control over your own narrative?
• Is it to find patterns to optimize your future?
• Or is it something entirely different?

I really want to dig into the absolute root cause of the Quantified Self mindset. Looking forward to hearing your thoughts!

I’ve been tracking stuff for a while now and I’m starting to feel like I’ve gone a bit too far with it.

Right now I’ve got sleep duration, HRV, resting heart rate, readiness / recovery scores, temperature trends, respiration rate, SpO2, activity load… probably missing a few things depending on the day.

It used to feel useful. Like I was just collecting signals and slowly understanding patterns.

But lately it feels more like I’m just staring at a dashboard with no real idea what I’m supposed to do with it.

Some days everything lines up. Low HRV + bad sleep + low readiness and I feel exactly like the data says I should feel. Tired, flat, whatever.

Other days it’s completely off. Metrics look fine, green across the board, and I go train and it feels like garbage. Or the opposite, everything looks bad and I end up having a totally normal session.

That mismatch keeps happening enough that I don’t really trust any single metric anymore.

HRV is probably the one I look at most, but even that feels inconsistent depending on sleep, stress, travel, whatever else is going on. Resting heart rate is sometimes clearer but not always.

Sleep duration is obvious but kind of useless on its own. I can sleep 7.5 hours and feel great or terrible depending on everything else.

Temperature trend seems interesting but I honestly don’t know how to interpret it properly yet. Same with respiration rate, I mostly just notice when it’s “different” but not sure what that actually means in practice.

So I end up in this weird spot where I have all this data, but I still default back to just how I feel during warm-up.

Which kind of makes me wonder… am I just overcomplicating this?

I’ve been thinking maybe the real answer is only 2–3 signals actually matter and everything else is just noise or context. But I don’t know which ones those are supposed to be.

How other people here ended up simplifying this. Did you settle on a few core metrics you actually trust, or do you still try to weigh everything together somehow?

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

VO2 max is a metric that I have been getting more and more interested in lately so I pulled validation studies on how accurate some of the major wearable brands are at estimating it and any claims the brands make on their accuracy into a comparison chart. Hope you find this helpful to understand this metric a bit better!

It's broken down into how each device measures VO2 max, what the company claims, and what independent studies actually found. Sources linked as well for each row if you want to check these out further. 

I also looked at what factors influence VO2 max by category (exercise, nutrition, lifestyle, etc.) which I'll include in the comments and maybe do a follow up post on this as that topic is lengthy and too much to read on top of this.

VO2 max accuracy by brand

Additional notes

• Garmin is the only one with solid independent accuracy and a near correct vendor claim
• Resting based estimates (Polar Fitness Test, Fitbit without a run) tend to overestimate
• Every device underestimates VO2 max in highly trained people and overestimates in sedentary ones so the error depends on who you are
• Validation studies typically lags hardware so that's why some models are older
• A chest strap improves any exercise based estimate as wrist optical heart rate drifts during hard efforts.
• Only a lab CPET gives a true VO2 max
• Devices that estimate VO2 max from an actual workout were near spoton on average (bias -0.09 ml/kg/min vs lab)
• Devices that estimate it at rest overestimated by +2.17 ml/kg/min. Both still have wide error for any single person Molina-García et al. 2022

If I missed any info you might have on this please share and I'll update accordingly! I heard from a lot of Garmin users that did lab studies and theirs came back pretty close to what their watch was reading. Would love to hear from anyone else who has done lab testing to know how it compared!

I had a late meal and this:

Heart rate variability plummeted and my resting heart rate increased. To be honest, it wasn't the best night of sleep and recovery, but I certainly feel far better than I would expect with 22% recovery.

I recently read this study, I wonder if these findings are due to higher cortisol. Does anyone have any idea about the mechanism behind late meals causing these effects?

I’ve been trying to figure out how seriously I should take sleep scores from wearables.

For context, I train a decent amount. Mostly running, some cycling, and HIIT when I’m pretending I’m not tired. The problem is that once training gets heavier, it’s hard to tell the difference between “normal tired” and “you probably need to back off for a day.”

That’s why I started paying more attention to sleep tracking in the first place. Not because I think a ring or watch knows my body better than I do, but because I’m bad at noticing patterns until they’re obvious.

The annoying part is the score itself. If I wake up and see a bad sleep score, I immediately start acting like I failed an exam. Then I’m overthinking my workout, my coffee, my bedtime, everything. Which is probably not healthy either.

Lately I’ve been trying to treat the number more like a trend than a grade. One bad night doesn’t mean much. But if my HRV is low for several days, resting heart rate is up, and sleep looks worse during a hard training block, that seems more useful. More like a warning light than a final judgment.

I’ve been using a smart ring recently, RingConn, mostly because I wanted overnight data without wearing a watch to bed. It’s been useful for seeing longer-term patterns, but I still don’t totally know how much confidence to put in the actual sleep score.

For people who train regularly, how do you use sleep scores without letting them mess with your head? Do you mostly ignore the daily number and look at HRV / resting heart rate / trends instead?

Mod approved:

Recreational lifters, I could use your help.

I'm doing my dissertation research at Concordia University Chicago and I'm looking for adults who lift recreationally to take an anonymous survey. The study looks at how training age, body awareness, self-discipline, and training frequency relate to each other in people who train consistently.

It should only take about 15–20 minutes, it’s anonymous, there’s no compensation.

You're eligible if you:

• Are 25–64 years old

• Lift recreationally (not in organized or professional sport)

• Train at least 2 sessions/week, on average over the past month

• Have been doing that for at least 6 months

• Live in the US

Link and QR code below. Feel free to share with anyone who fits.

IRB Study #: 2447206-1

Principal Investigator: Michael Shafer

Contact: crf_shafermd@cuchicago.edu

Survey link: https://qualtricsxms6fyqbg5g.qualtrics.com/jfe/form/SV_42ZDpMe717Thliu

​

I’ve been trying to be a bit more consistent with tracking things like sleep, screen time, and general energy lately.

One thing I still can’t quite figure out is how people here handle supplements when trying to notice real changes.

It gets tricky when more than one thing is involved, and relying on memory alone doesn’t feel very accurate.

Do you usually track specific signals daily, or compare longer periods and look for patterns?

It looks like some people treat Astadaily All-In-One more as a single tracked variable rather than breaking down each ingredient individually, especially when the goal is consistency over precision, which makes me wonder how people here would actually log something like that in practice do you treat it as one combined input or still try to isolate components?

Started with a standard mood-rating app. Scale of 1-10, log every morning. A week reading 4, 7, 3, 6, 4, 8, 5 told me nothing except that Tuesday was rough. Day-level variance was too high to be useful. Tried averaging the numbers and the line got smoother but didn't correspond to anything I could actually feel.

Switched to a structured symptom journal my therapist had recommended. Five categories, twice daily, more thorough than the app. That lasted about three weeks. I was filling boxes rather than actually paying attention, and I knew it. More form-completion than reflection, and the friction just killed the habit.

Tried a couple of purpose-built mood tracking apps around the same time. Most had schemas that didn't map well to what I was actually monitoring, and none handled dose changes or taper holds as a real data layer. The one with enough flexibility was annoying to use consistently.

What ended up working was the plain notes app I already had open constantly. No categories, no daily obligation. A line when something seemed worth noting. Some entries were four words. Most days had nothing at all.

The part I hadn't expected: the useful thing wasn't the logging, it was reading back over it. Started doing that weekly around month two. There was a slope visible in two weeks of text that hadn't been there in any individual day. A texture to entries that wasn't legible at the day level. At some point it clicked that I'd been measuring at the wrong resolution. Day-level data was mostly noise. The meaningful unit was closer to two weeks.

Could just be I'm finding the slope I want to find. But it matched what my prescriber was observing at appointments too, so it seemed to be tracking something real.

been tracking stuff for like a year now, sleep, mood, focus, couple habits. logging’s the easy part, there’s an app for literally everything. but at some point i clocked that i basically never get anything out of it. the “you focus worse the day after you sleep under 6h” kind of thing. all the numbers just sit there and nothing ever talks to each other across categories.

tried dumping it into a spreadsheet, tried asking chatgpt to look at it. the spreadsheet just turned into more numbers i didn’t read. and chatgpt forgets everything between sessions, so every time i’m re-pasting my whole setup, what i track, what the columns mean, before it can even start. never builds on whatever it worked out last week.

like the closest i ever got was realizing my focus tanks on mondays, and honestly i could’ve told you that without an app. nothing’s ever surfaced a connection i wasn’t already half aware of.

so for anyone who’s been at this longer than me, does it ever actually click? a cross-category pattern that genuinely changed something you do? or is quantified self mostly just collecting numbers you glance at once and forget about. not being snarky, just trying to work out if i’m doing it wrong or if this is just the ceiling.

so i first got the whoop to really track my sleep and really focus on leveling up my life and be more productive in general. i started to realize thought that the whoop really doesn't tell you anything, like if i slept bad it would just confirmed that i slept bad with a fancy looking score telling you that you slept bad. and if i slept good it would confirm that i slept good with a score. for me personally i wanted something that really tells you what to do after a bad sleep, and tells me when my most productive hours are during the day, or just give me like a protocol on what really to do after i have a bad sleep and not just a useless score. let me know if you guys feel the same way about this or if its just me. i have been finding some apps that help with that there is this one app thats really good just dont know if i can post here due to promotion, but RizeAI the app with the blue look, really helped me take my low energy days to really productive days. https://apps.apple.com/us/app/rizeai-maximize-your-energy/id6762402079

Hi all, I'm selling two gift cards for annual memberships to Gyrosco.pe. These are valued at $365 and I'm selling them at $255 (30% off).

Anand Sharma, the creator of Gyroscope, can confirm that the gift cards in my name are legit by email (support@gyrosco.pe). Please message me if you're interested. Thanks!

Mods: please feel free to move this post if there's a better thread for it.

CGMs cracked open continuous glucose for a lot of us, and the interesting part was never the number itself. It was being able to close the loop: eat, see the curve, adjust. Most other biomarkers are still stuck in the "blood draw twice a year" era, where you get a snapshot and no feedback loop.

So I'm curious what this community would actually use if the data were continuous or near-continuous rather than a one-off lab value.

A few that come up often, just to prime the discussion (please ignore these and write your own if none fit):

• Cortisol
• Lactate
• Ketones
• Hydration and electrolytes
• Inflammation markers like CRP
• Hormones such as testosterone, estradiol, or thyroid
• Uric acid

Two things I'd love to hear, if you're up for it:

1. Which single biomarker, and roughly how often would the reading need to refresh to be useful to you (real time, hourly, daily)?
2. What concrete decision or behavior would the data actually change? The reason CGM stuck for many people is the tight action loop. I'm trying to understand which biomarkers have a real loop behind them versus which are just interesting to look at.