An Automatic Radial Pulse Signal Acquisition System Based on Visual and Tactile Pulse-Finding Algorithm

The radial artery pulse signal contains rich information about human health status and diseases. Currently, most acquisition systems take the form of fixed acquisition positions that cannot automatically locate and collect the pulse and require manual assistance. However, due to variations in human wrist anatomy, these systems face challenges in ensuring consistent and repeatable positioning for each pulse collection, which may affect the quality of pulse signals. To overcome these limitations, this article develops an automatic pulse signal acquisition system based on a combined visual and tactile pulse-finding algorithm. It can identify the strongest pulse position through a lightweight pulse localization network (LPLN) and automatically acquire pulse signals. In addition, the system can further refine the identification of the strongest pulse position through a tactile pulse-finding method based on time- and frequency-domain characteristics. The adjusted position can serve as training data for LPLN self-learning. The experimental results show that the average error of LPLN visual and tactile pulse-finding algorithm localization is 4.07 and 1.36 mm, respectively. The proposed prototype may serve as a valuable tool for intelligent pulse signal acquisition, guaranteeing accurate location and signal quality.