Data Analytics & Rehabilitation Technology (DART) is an academic research lab generating clinical evidence from large-scale behavioral health data derived from continuous sensor-based, clinical, and contextual measurements. We use these data to enable precision medicine by linking individual behavioral signatures to adaptive, closed-loop health intervention strategies. We study conditions where health outcomes are highly variable and population-level approaches fail to capture individual needs. By modeling behavior continuously and at scale, we aim to predict how health trajectories are shaped at the individual level and to derive personalized intervention strategies that respond to moment-to-moment behavior and clinical context.

DART works in close partnership with clinical partners to translate these models into deployable, personalized rehabilitation and prevention approaches. Our technology-first research environment integrates real-world data acquisition, analytics, and intervention design within tight development and clinical feedback loops. These efforts are supported by integrated technology and data platforms, access to unique real-world and clinical health datasets, and scalable on-premises computing infrastructure for model development. This enables systematic evaluation of personalized interventions in clinically relevant settings and supports the generation of robust, generalisable evidence for next-generation precision medicine.

By reducing unexplained inter-individual variability in rehabilitation outcomes, DART’s work aims to strengthen the evidence base for precision medicine and contribute to more effective, efficient, and equitable healthcare delivery.