I'm trying to improve access to raw data, expand the sensing modalities, and improve data quality for studies in to diseases that can present through cardiovascular mechanisms.

If you’ve done research with wearables, I’d be interested to hear what the biggest limitations were for you, as well as any general advice!

I used to be a biomedical postdoc, then medical device engineer, it was so difficult to do wearable research at scale unless you were inside one of the big companies, you could buy the devices, but getting to the raw data was often impossible, and there were always data dropout issues over longitudinal studies. I suspect it's partly because the hardware and systems are designed primarily for low cost consumer applications rather than open ended research, whilst companies also see the longitudinal data sets as very valuable and are reluctant to make them fully accessible. So I'm trying to build something more research focused.

I've been writing about the embedded C side of the project as I go: https://skoopsy.dev

Rust looks very cool and is probably the future. To lower complexity it seems to make sense for me to stick with the familiarity of C from a bunch of Arduino projects (Although mostly Arduino IDE and Libraries) and some C++ projects (not embedded), but maybe I don't know what's good for me there, is there an equivalent to shooting yourself in the foot or blowing your whole leg off in Rust?

It seems to make sense to dabble with registers enough to be confident in understanding what the HAL is doing whilst learning, I find taking a peek at the lower levels of abstraction can really impact how to use libraries best?

"Reference Manual" - Brilliant! Just took a look and this is going to help me get my bearings so much, thank you!

STM32 family is definitely overwhelming - I was tempted to pickup a F0 Nucleo to match the tutorials but I'll take that advice and stick with the F1 Nucleo that was given to me.

Comments URL: https://news.ycombinator.com/item?id=43372792

Points: 10

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