Digital Health Monthly: Scientific Webinar Series
Achieving Data Compatibility and Navigating Hardware Evolution Across Sensor Generations with Confidence
Tuesday, July 28, 2026 @ 12 PM ET
Upcoming Digital Health Monthly:
Scientific Webinar Series
Accelerating DHT Research and Drug Development with Open-Source Big Data from Population Studies
Tuesday, December 3 @ 12 PM ET
Digital Health Monthly: Scientific Webinar Series
Sensor-based DHTs are shedding an illuminating light on how people function in their real-world environments. Drug developers, researchers, patients, and regulators are realizing the multifaceted value sensor-based DHTs can bring to clinical research.
As their adoption continues to grow, the ActiGraph team is excited to continue ‘Digital Health Monthly’, a monthly series of science-focused webinars to share the latest high-impact developments in clinical research from innovators in the digital health field. Each month, we feature brief data-driven presentations from clinical researchers, data scientists, and biostatisticians on a focused topic with dedicated time for audience Q&A. We believe that together, we can move the digital health technology field forward faster, and we are excited for this opportunity to facilitate important discussions on the latest research with members of the digital health community.
Long-term clinical protocols and multi-year epidemiological cohorts face an inevitable operational hurdle - hardware obsolescence. Over a multi-year or multi-phase study, switching wearable device models is a logistical hurdle faced by many. Yet, there remains a major industry tension and scientific skepticism among end-users, key decision makers, and regulators balancing preferences to lock in a single hardware model with the practical necessity of upgrading sensors.
Grounded in the Digital Medicine Society’s (DiMe) V3+ framework, this 60-minute live webinar outlines a blueprint demonstrating that the key to changing devices confidently lies within the raw data itself and the strategic deployment of standardized post-processing methods.
Learning Objectives:
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Learn the translation of findings from benchtop sensor verification to analytical validation under the DiMe V3+ framework.
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Understand how data formatting and algorithmic calibration can help resolve underlying hardware discrepancies.
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Gain actionable strategies to confidently upgrade wearable sensors without breaking mid-study data compatibility.
