Achieving Data Compatibility And Navigating Hardware Evolution Across Sensor Generations With Confidence

Wearable devices inevitably become outdated during long-running clinical trials and epidemiological cohorts, forcing study teams to choose between locking in aging hardware or risking data continuity by switching to newer sensors. This tension creates real uncertainty for study teams, sponsors, and regulators alike, particularly when device changes could compromise data comparability across study phases. This 60-minute webinar offers a practical path through that uncertainty, grounded in the Digital Medicine Society's (DiMe) V3+ framework. Attendees will learn how benchtop sensor verification findings translate into analytical validation, how algorithmic calibration addresses hardware-level discrepancies, and how to build a defensible strategy for upgrading sensors mid-study.