The Effects of AI-Guided Exercise and a Smart Ring on Arterial Stiffness (GONDOR-AS): protocol for a randomized controlled trial

BackgroundCardiovascular 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 artificial intelligence (AI) -based coach personalized for individual data and preferences could be a powerful, low-barrier tool for achieving sustainable cardiovascular health benefits by directly addressing the adherence challenge. ObjectiveWe will study the comparative effectiveness of a wearable and an interactive app-based AI coaching intervention promoting moderate exercise on 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 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. MethodsThis randomized controlled trial recruited 165 eligible sedentary participants aged 30-65 years. Co-primary outcomes cfPWV and VO2max were measured at baseline and will be repeated after 12 weeks. Participants were equally randomized into three groups: an AI-based coaching group (steady-state exercise), a HIIT group (supervised exercise) and a control group (usual low activity). The AI-based coaching group receives personalized guidance using large language model (LLM) technology. All participants wear Oura Ring and are blinded to cardiovascular health metrics provided by the ring. ResultsThe 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 early 2026. Data collection is ongoing. ConclusionsThis study will evaluate if a highly scalable, AI-based coaching intervention can achieve comparable gains in CV 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. ClinicalTrials.gov registration identifierNCT06644014 (Registered: 2024-10-15)