From lab to life: Wearables, real-world data, and the future of autonomic research

Traditional methods for assessing autonomic nervous system (ANS) function are constrained by conventional clinical settings, limited timeframes, and exclusionary protocols. These limitations prevent the accurate capture of dynamic physiological fluctuations, particularly in underserved populations and those with complex or rare autonomic disorders. This paper outlines how wearable technologies and mobile health (mHealth) platforms are redefining the landscape of ANS research. By enabling continuous, real-world monitoring and integrating multimodal data, including comprehensive physiological and behavioral signals, patient-reported outcomes, these tools offer unprecedented opportunities for personalization, decentralized and pragmatic clinical trial designs, and enable early detection and intervention. We examine the evolution of wearable sensors, the role of artificial intelligence in translating raw data into clinically actionable insights, and the economic and equity implications of digital-first research. With regulatory momentum growing and real-world evidence gaining traction, the convergence of wearable technology and autonomic science signals not just a methodological shift, but a fundamental redefinition of how, where, and for whom clinical science is conducted.