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Comment by scheme271 | Hacker News Reader

I'm not sure the body battery/stress measures are that great. Garmin is infamous for having an awful sleep algo and it still has a lot of trouble detecting naps. It doesn't bode well for being able to get stress data. I think it's good for generally determining high stress vs low stress and when you've overdone exercise recently but probably not much more.

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Body battery is amazing. I had long COVID/ME/CFS, and looking at the body battery when waking up was an outstanding predictor of how my day was going to be. When I hit 5% body battery, I was really feeling horrible.

It's just a collation of sleep-end RHR/HRV. It's completely trivial and many manufacturers do this correctly; both are extremely reliable predictors of recovery metrics.

Garmin has absolutely shitty sleep tracking but it doesn't matter; any wearable more or less nowadays can get static heart rate correct, leading to more or less accurate recovery metrics.

"Collect every paper you can find on RHR/HRV/etc. recovery metrics. Develop an algorithm for predicting recovery score per day based on the research" as a prompt to a Codex or Claude agent can probably get you 98-100% of the way there.

Edit: As a proof of concept, I had ChatGPT Pro 5.6 write the algorithm with my Fitbit data. Looks great.

Do you have a particular hardware sensor requirement needed to clone the body battery function? I’m interested in developing this too but always resisted getting a smartwatch due to privacy concerns. If there’s something available that’s Gadgetbridge compatible I’d be very interested.

Good news; I'm gifting you with the fruits of AI, that has collated 200+ papers on the topic. I know, I know; this is generous.

https://github.com/catigula/recovery

Incredible thank you!

I’ve had Claude work on a body battery type solution, which I’ll fully deploy over the coming days. It’s to manage and track brain fog/long COVID type symptoms and see if there’s correlation between foods eaten the day prior, resting heart rate etc and perceived brain fog. I’ll see if it’s possible to incorporate some of your work into my solution too.

It took GPT-5.6-Sol Pro about an hour of work; don't thank me :P

How does HRV predict stuff like this ?

Good news; I'm gifting you with the fruits of AI, that has collated 200+ papers on the topic. I know, I know; this is generous.

https://github.com/catigula/recovery

HRV is an indicator of how much stress you are experiencing. The variability increases when you are more relaxed and under less stress and decreases as your stress level increases. The relationship is a bit counterintuitive but it's a thing.

Interesting. What did you have to do to "charge" the body battery tough? And how does the garmin keep track of that?

Naps and rest “charge”, and yes, Garmin keeps track of that.

Not that I put a whole lot of weight in those data personally.

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