Real-time tracking of radial artery vessel wall using a Kalman filter-based ultrasound single-plane wave RF signal time-frequency information fusion algorithm

Objective The goal of our study was to achieve real-time dynamic tracking of the radial artery vessel wall in everyday life, which is crucial for blood pressure estimation and cardiovascular disease prediction. Methods The algorithm integrates time–frequency information from ultrasound single-plane wave RF (radiofrequency) signals and consists of three main components: feature frame ROI (region of interest) selection, inter-frame cross-correlation and intra-frame autocorrelation, and feature frame Kalman filtering. Results Experimental validation on a silicone gel ultrasound phantom with simulated blood vessels demonstrates an average diameter estimation error of less than 0.5% compared to ground truth values. Comparative experiments show similar relative errors (2.83%, 2.43%) to the optical flow method, with a computational speed 7.32 times faster. The algorithm accurately aligns extracted pulse waves with pressure pulse waves at six local feature points per cycle. Conclusion The proposed method achieves a favorable balance between speed and accuracy in tracking the radial artery vessel wall. It holds significant potential for real-time monitoring of physiological health parameters, offering precise and dynamic tracking capabilities. Significance This algorithm addresses the challenges of non-invasive real-time tracking, benefiting blood pressure estimation and cardiovascular disease prediction. Its integration of time–frequency information and efficient computational speed make it valuable for the scientific community and public in monitoring physiological health parameters.