Garbage in, Garbage out: A Look at Misinterpretations from Oura

This morning, my Oura ring yet again expressed concerned for my well-being. For the past week, my temperature has been higher than baseline, which for Oura means that I'm likely fighting off something nasty and should take it easy.

And yet, I feel better in many ways than I have for years. How is this possible?

Oura only reports temperature relative to your own average. This is for no other reason than if they were to report an actual number, Oura would then technically become a "medical device," subject to a whole slew of extra regulations and restrictions.

So your temperature is reported as + or - your baseline.

And while seeing your temp compared to your baseline has value, it's missing crucial context that would come from also knowing how it compares to people of your age and gender in general.

Personally, I've run a low temperature since I was kid. Typically, about 97.4 F / 36.3 C. This was brutal when I would have a fever, which might register at about 99 F / 37.2. High enough to feel truly like garbage (and probably be contagious) but not objectively high enough for my physician mother to agree I should stay home from school to recuperate.

Which now brings me to my Oura. Ironically, it's providing the relative assessment without the objective one that missed my true condition in childhood. It's raising concern about a consistent relative increase without the awareness that this is bringing me to a healthier baseline.

It should be giving me a high five! "What've you been doing differently, Mel? Because it's working!"

Out of curiosity, this morning I took my objective temperature with an official "medical device" thermometer. 98.0 F / 36.7 C. Cause for concern? Spiking a fever? Fighting off something horrible? Need to lie down? I think not.

Moving towards a healthier baseline as I continue to address triggers of ill health? Oh yeah.

On deeper inquiry, I've found that practically none of the messages from wearables can be taken at face value without understanding what's driving the interpretation. This has spurred me to look under the hood at the data to understand what they're basing the interpretations on. This is a fairly straightforward exercise in the case of temperature reporting. Way more complicated in the case of HRV, which I've written about elsewhere.

So whether you're trying to "biohack" your health, improve your performance, or recover from a complex chronic illness, be sure to not over-relay or over-estimate the objective accuracy of your wearable unless you fully understand what's going on behind the scenes.

If you're not looking at the data itself, then beware that if the algorithm is too narrow to apply to you, then it'll be a case of "garbage in, garbage out."