From frailty-driven to frailty-informed care in the age of wearable AI

Abstract

As populations age, frailty is increasingly monitored through wearable technologies capable of continuously capturing behavioral and physiological change. While these systems enable earlier detection of vulnerability, they also risk transforming probabilistic signals into rigid clinical thresholds. We propose a frailty-informed framework in which artificial intelligence (AI) augments, rather than replaces, clinical judgment. By integrating longitudinal digital monitoring with multidimensional geriatric assessment and bedside evaluation, this approach supports anticipatory, patient-centered care. Proportional design, transparency and clinical oversight are essential to ensure that predictive systems guide care without narrowing therapeutic options. Bignami et al. present perspectives on integrating wearable technologies and artificial intelligence in frailty monitoring. They propose a framework that is frailty-informed to augment clinical decision-making.