The Effects of AI-Guided Exercise and a Smart Ring on Arterial Stiffness: Protocol for a Randomized Controlled Trial

Abstract

Abstract Background Cardiovascular disease (CVD) prevention is limited by the major challenge of low long-term adherence to effective lifestyle regimens. Arterial stiffness (measured by carotid-femoral pulse wave velocity [cfPWV]) and maximal cardiorespiratory fitness (measured by VO2max) are modifiable risk factors for CVD but require sustained lifestyle change. Wearable technology provides continuous measurement and offers a scalable platform to deliver health interventions. A combination of continuous monitoring with a wearable device and an AI-based coach personalized to individual data and preferences could be a powerful, low-barrier tool for achieving sustainable cardiovascular health benefits by directly addressing the adherence challenge. Objective We will study the comparative effectiveness of a wearable and an interactive app-based AI coaching intervention promoting moderate exercise in improving gold-standard cfPWV and VO2max. This will be compared to a supervised high-intensity interval training (HIIT) group (benchmark with known benefits for VO2max) and a control group using only the Oura Ring (passive monitoring). We will also conduct a detailed process evaluation (structured interviews) to study the feasibility and experience of interacting with the AI coach. Methods This randomized controlled trial will recruit 165 eligible sedentary participants aged 30 to 65 years. The co-primary outcomes, cfPWV and VO2max, are measured at baseline and will be repeated after 12 weeks. Participants are equally randomized into 3 groups: an AI-based coaching group (steady-state exercise), an HIIT group (supervised exercise), and a control group (usual low activity). The AI-based coaching group receives personalized guidance using large language model technology. All participants wear the Oura Ring and are blinded to the cardiovascular health metrics provided by the ring. Results The recruitment for the study began in October 2024 and will end when 165 men and women have been recruited. Data collection for the study is scheduled to conclude in early 2026. Data management is ongoing. Conclusions This study will evaluate whether a potentially highly scalable, AI-based coaching intervention can achieve comparable gains in cardiovascular structural health (cfPWV) and functional capacity VO2max relative to a resource-intensive supervised HIIT benchmark. The findings will provide essential evidence on the use of digital health tools to promote sustainable exercise adherence.