Contactless 12-lead electrocardiogram via deep computational radar

Cardiovascular disease (CVD) remains the leading cause of global mortality, highlighting the need for scalable, continuous, and contactless diagnostics. Traditional electrocardiogram (ECG) systems, though essential for detecting cardiac abnormalities, are constrained by contact-based, intermittent measurements. In this work, we introduce CardioRadar, a clinically validated radar-based system for contactless 12-lead ECG monitoring. Compact custom radar hardware captures chest micro-motions induced by cardiac activity, while data-driven inverse modeling reconstructs electrical signals from mechanical motion. Validated in 6974 individuals across diverse clinical settings, CardioRadar achieves a mean correlation of 0.75 (median: 0.77), RMSE of 0.09 mV (median: 0.07 mV), and inter-beat interval error of 23.39 ms (median: 5.60 ms) compared to ground-truth ECG. It also reliably detects arrhythmias and supports continuous overnight monitoring. CardioRadar represents a transformative, low-cost solution for equitable, long-term cardiovascular care.