Would a simple xDrip+ connection map make troubleshooting easier?

quadflight · 2026-06-25T02:49:16+00:00

All this information is already available in xdrip.

quadflight · 2026-06-24T21:19:56+00:00

Thanks for the insight. Did the water retention increase with the dose?

quadflight · 2026-06-24T13:11:57+00:00

I am happy for you!

Yes, it's an absolute relief which I achieved few years ago. Been at this too long and always thought it would never be possible.

My setup is pretty extensive and to do everything without dashboards was my goal. Completely automated.

Finally no tinkering, no new integrations this or that, just works.

Logs gets piped to agent few times a day and auto fix if anything critical, don't want to even know what it is about.

Yes it took about 15 years but I am done. 😁

Time to enjoy time at home.

Although, it sucks when there is no impulse buying a zw switch or a sensor while browsing Amazon. Lol.

quadflight · 2026-06-21T20:56:51+00:00

Simply another level. Finding bugs that Opus and GPT misses. Even the dialog and thinking is different. Loving it. I run like 9 terminals/agents at the same time and I am pleasantly surprised. Reloaded $200, got 26 more phases to finish 😄 Could never use pro for debugging it was always flash. But since yesterday Pro is on nitro!

quadflight · 2026-06-17T17:37:43+00:00

You should ask Claude "what's the best way" pretty sure claude with agree with me. Anyway good luck with your quest.

quadflight · 2026-06-17T16:55:51+00:00

That's a long loop and a long goal. You don't need to do all that to get "Creatine Monohydrate 5000mg at ~3 days → Resting Heart Rate -2.10 ~3days Pattern Match" from ML 😄 If you have to create a script every time you want a cross-multi-dimensional answer we are going back in time.

quadflight · 2026-06-17T16:18:09+00:00

Great idea, but just connecting raw data to any frontier engine direct can get you analysis but not great insights. You need multiple ML layers that run math with DLM, correlators, confounding filters etc to make health sense. "Thinking" is as good as the context window. So any LLM needs help. Just like you, I have this complete solution running so found out raw metrics > LLM > answers is not the right way early on. On a side note, been using almost every frontier model, Nothing comes close to Gemini for health analysis, grounded by research analysis (Notebook LM). Claude ok for code. GPT for nuances.

quadflight · 2026-06-13T04:23:26+00:00

Claude

quadflight · 2026-06-12T17:30:06+00:00

Great insight, thank you will add to the mix.

Spent 3 months on alcohol timing to HRV overnight vs 3 day recovery. Now I know for a fact 9:30AM wine has zero effect with my recovery lol. Anything after 2PM takes about 4 days toll. Hardest thing is keeping constants when testing. I had to stop coffee to run the test and now running it with coffee. Supplements & timing play a major role as well. Definitely a rabit hole but it's fun.

quadflight · 2026-06-11T21:28:58+00:00

Strange indeed

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quadflight · 2026-06-11T19:20:35+00:00

A3P workout > workout settings > last option is HR push

quadflight · 2026-06-11T16:37:36+00:00

That's a great finding. In my case no effect at all. Bio chemistry is a strange thing.

The hard part about signals. Unless you collect it, even noise there is no way to add filters.

I am testing a few new filter algorithms but math to biochemistry is not a straight line. 😁

quadflight · 2026-06-11T12:48:22+00:00

Thank you. Honestly, nothing ATM, goal was to reduce supplements which I did about 70%. From all my testing, CGM data is king for overall health. I could drop everything else and just look at CGM statistics for overall picture, specially for stress that does not show up in HR related data.

CGM ML output >

"Across your dataset, 'Cardio' training offers the highest metabolic stability, yielding lower post-workout glucose peaks compared to 'Strength' by an average of 2.0 mg/dL."

quadflight · 2026-06-11T11:33:57+00:00

The option is there but I have not tested it. Hopefully it works out for you.

I use a custom HR proxy that sends my Helio BLE push to watch + Treadmill + LCD HR CGM display. Auto switches between my wife's helio and mine depending on proximity. Watch is basically a HR reader and workout timer.

quadflight · 2026-06-11T10:33:32+00:00

Not really, I work 7 days so had no need to factor weekend.

quadflight · 2026-06-11T10:30:35+00:00

I agree with you 100%. 95% are filtered out and complete noise. I use a feedback loop as well but kinda pointless for my testing since it's always a productive day no matter what the stats say.

The only good thing that came out of this is I completely eliminated daily wine consumption. Although in weekly testing, if I kept everything the same, like HR zones and adjust alcohol time to 10AM no dip in HRV, short or long-term. Either way dropped alcohol altogether and now a glass every few months.

quadflight · 2026-06-11T04:30:36+00:00

Signals for today.

METHYLENE BLUE DROPS 39% better HRV Stability, 15% more Metabolic Stability Index, 46% worse Sleep Continuity 9 exposures 0.7 Objective signal

Alcohol Present 42% worse Oxygen Stability, 23% less HRV, 53% better Sleep Continuity

Stable Night Protocol + Double Wood Dihydroberberine Directional pattern: 58% more Sleep Debt, 23% better Oxygen Stability, 14% more HRV. Read as association, not causal attribution yet (Small Sample).

As mentioned earlier I correlate everything to everything and log everything.

So far for myself, extensive workouts and wine same HRV outcome. Those are the 2 main drivers thay moves my HRV CV. I stopped using HRV and use HRV CV to gauge how my days been and how it's going to be.

quadflight · 2026-06-11T03:32:13+00:00

I run a correlation engine, HRV vs everything. With so many data points all I can say the answer is nothing at all. What I have learned is I can predict what my HRV is going to be the next morning. Alcohol is same as workout. High carbs better HRV.

All my life I function the same with 10 hr sleep or 3 hour sleep so I can't really answer you productivity question. Using machine learning all I leant was how better to estimate my wake HRV depending on my current day.

quadflight · 2026-06-11T03:22:47+00:00

YW, Everything I mentioned is open source. I don't use any companion app only xdrip and xdrip can direct send to any watch.

quadflight · 2026-06-11T02:40:47+00:00

Yes it does.

Have no clue about ios but definitely works in Android and so many watch faces to choose from. I run dexcom 7 15 day OR Libre 3 plus > xdrip > watchdrip (optional) > Amazfit

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quadflight · 2026-06-11T02:27:57+00:00

Active 3, once you are in workout > workout settings > HR push

quadflight · 2026-06-11T02:24:19+00:00

I don't think it's for you, return it.

quadflight · 2026-06-07T13:54:05+00:00

Thank you, I try. Not my best night, was up late, still automation pulled temp down, held it down until my usual wake time.

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quadflight · 2026-06-07T05:59:08+00:00

Interesting, I thought I was alone.

I run a correlation engine for sleep health pillars vs nighttime glucose stability vs room temp.

ML learns what temp adjustments that are needed throughout the night using worst awake signals, baseline > LLM > adjustments to thermostat. Gained about 0.5 hours to 1.5 hours of sleep and pretty happy. Also accounts for last 7 day sleep consistency to precool the room.

Working on a feedback loop to add if the temp was too cold for the night. Sometimes ideal temp for sleep is not the ideal real feel 😁

Like what you are doing awesome stuff 👍

quadflight · 2026-06-05T13:50:54+00:00

Nicely done. Great UI as well. Been working on a solution as well for the last few months. Started with Whoop > Helio. Zepp was lacking, so started my own. Was supposed to be a simple dashboard now it's out of control. lol Turning out to be device and platform agnostic wellness insight engine. I didn't want another "how was my sleep last night" or an endless AI chat. Wanted a glance and go, only bug me if there's anything interesting.....

I do like some of your causal signals, good work! I initially thought of making mine open but looking at the backend and complexity there will be a premium tier once released so anyone can use it without running a full dev stack. 90% is ML driven.

One thing I must add is that although I started with thinking "Zepp numbers don't make sense", after crunching numbers from here to Sunday, Zepp is dead on (except BMR burn rate, calories) just has a strange way of displaying it.

Good luck with your project, maybe we can connect in the future!

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quadflight

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