Concerning data from wearables Region Östergötland in Sweden has done some work, including exploring openEHR data structures and also student projects from Linköping University created webapps for extracting and filtering/summarising data from Google Fit and storing in an openEHR CDR.
Feel free to pick up the stalled Discourse thread: Physical activity archetypes; exercise, steps etc from apps & devices
…and perhaps have a look at the student projects linked from GitHub - regionostergotland/Physical_activity pages 28+ in the initial student report contains some screenshots.
Regarding decision support based on personal wearables, “digital twin” technology may be even more interesting than GDL. Gunnar Cedersund’s research group at Linköping University do some cutting edge stuff there.
If you want to follow clickable links in the image below, it is slide #30 from 2020-12-07-Vebjørn+Erik-openEHR-Norwegian-archetype-governance-v4.pptx - Google Präsentationen
Translation hints: tvilling = twin, ofiltrerat = unfiltered, filtrerat = filtered, berikat = enriched, självvald lagring = (patient’s) own choice of (private) storage, Regionens lagring = Storage at helathcare provider/region
