Rationale and design of the AutoHealth study: prospective clinical validation of continuous multimodal in-vehicle health monitoring in real-world mobility.

AIMS: Continuous physiological monitoring outside clinical environments remains limited by usability, reproducibility, and user adherence. Vehicles offer a semi-controlled setting enabling unobtrusive multimodal sensing during everyday mobility. The Automotive Health Proof of Concept Trial (AutoHealth) investigates the real-world feasibility and accuracy of continuous in-vehicle cardiovascular monitoring using integrated optical, electrical, and acoustic sensors benchmarked against medical-grade reference standards.

METHODS AND

RESULTS

AutoHealth is a prospective, observational cohort study at Charité - Universitätsmedizin Berlin enrolling adults across five predefined cohorts: healthy individuals, patients with an elevated cardiometabolic risk, HFpEF, HFrEF, and persistent atrial fibrillation. Participants undergo comprehensive baseline phenotyping followed by a structured in-vehicle session comprising static and dynamic driving segments and predefined physical and cognitive stress tasks. Synchronized biosignals including rPPG, steering-wheel ECG, phonocardiography, and voice-derived features are compared with clinical reference measurements. The primary endpoint is the median absolute percentage error (MAPE) of in-vehicle vital sign estimates vs. reference measurements, with successful performance defined a priori as MAPE ≤10%. Secondary endpoints include the proportion of measurements meeting predefined clinical accuracy thresholds, arrhythmia detection performance, characterization of autonomic stress response, and correlations with functional mobility metrics. The study adheres to STROBE and SPIRIT-AI guidelines and is registered in the German Clinical Trials Register.

DISCUSSION: AutoHealth is designed to provide a prospective clinical validation of continuous multimodal cardiovascular monitoring inside a modified production vehicle under real-world driving conditions and reproducible closed-course testing. Study findings will characterize feasibility, performance, and translational potential of Automotive Health as a scalable prevention and remote physiological monitoring paradigm.