Traditional Human Activity Recognition (HAR) utilizes accelerometry (movement) data to classify activities. This summer, Team #4 examined using physiological sensors to improve HAR accuracy and generalizability. The team developed ML models that are going to be available open source in the Digital Biomarker Discovery Pipeline (DBDP) to enable other researchers and clinicians to make useful insights in the field of HAR.
Project Lead: Jessilyn Dunn
Project Manager: Brinnae Brent
Watch the team’s final presentation (on Zoom) below: