Millimeter-wave Radar Heart Rate Estimation Method Based on Parameter-adaptive Multivariate Variational Mode Decomposition

Heart Rate (HR), a core physiological indicator of human health, is of substantial clinical importance when accurately monitored in applications such as arrhythmia screening, early warning of coronary heart disease, and chronic heart failure management. However, cardiac echo signals are susceptible to coupled disturbances, including respiratory motion artifacts and environmental electromagnetic interference, which degrade the signal-to-noise ratio and compromise HR estimation accuracy. To address these challenges, we propose a multi-channel joint HR estimation method based on multivariate variational mode decomposition that exploits shared cardiac information across different channels. Specifically, the proposed method first constructs a multi-channel joint optimization model that minimizes the total modal bandwidth under reconstruction residual constraints. It then adaptively initialize the center frequency by leveraging the cumulative effect of multi-channel spectral peaks, enabling robust separation of heartbeat modes with consistent frequencies across channels. Finally, the HR mode is selected from the decomposed modes using a maximum energy criterion to complete HR estimation. Validation on real-world data from six subjects demonstrated that the proposed method achieves a median HR error of 1.53 bpm, outperforming conventional single-channel approaches and existing multi-channel fusion-based HR estimation methods.