(OP here) I worked on one of the first studies on detecting diabetes from wearables in 2018. It was kind of fun to review how the field has evolved. The basic approach is the same (pretrain a self-supervised foundation model on sensor data, fine-tune for a particular application) but the scale is several orders of magnitude larger.
It seems their algorithm wouldn't work for me -- it would rate me falsely insulin insensitive:
> " Google’s study found the expected pattern: HOMA-IR rose with resting heart rate (r = 0.27) and fell with daily steps (r = -0.25) and HRV (r = -0.14)."
I have unusual chronic sympathetic nervous system stimulation such that my RHR is +90 even during sleep and my HRV is 8-13ms, despite ~2hr daily exercise.
My actual HOMA-IR values were so low they were _below_ the reference range, the exact opposite of what this model would predict:
(OP here) I worked on one of the first studies on detecting diabetes from wearables in 2018. It was kind of fun to review how the field has evolved. The basic approach is the same (pretrain a self-supervised foundation model on sensor data, fine-tune for a particular application) but the scale is several orders of magnitude larger.
It seems their algorithm wouldn't work for me -- it would rate me falsely insulin insensitive:
I have unusual chronic sympathetic nervous system stimulation such that my RHR is +90 even during sleep and my HRV is 8-13ms, despite ~2hr daily exercise.My actual HOMA-IR values were so low they were _below_ the reference range, the exact opposite of what this model would predict:
https://i.imgur.com/ISEwgAl.png
Curious-is there a particular diagnosis they should be compensating for in these algorithms?