3DP Code-Based Compression and AR Visualization for Cardiovascular Palpation Training

Zhendong Chen, Bo Peng, Kaifeng Gong, Yinan Hao, Xiaohua Xie

Abstract: This paper introduces an augmented reality (AR) visualisation based on the three-dimensional palpation code (3DP code) to enhance palpation training in cardiovascular examination. Traditional palpation training methods, such as textbook descriptions and subjective evaluations, may fail to adequately differentiate between tactile image patterns under varying vascular conditions. Moreover, the large amount of data involved in creating dynamic 3D tactile images for palpation complicates their storage, transmission, and display. Our method, demonstrated using a typical artery palpation example, provides interactive 3D visualisations and interactions, accompanied by efficient encoding, decoding, and compression techniques for large tactile data sets. Assessment results show a data compression ratio of 1/360, preserving over 95% of physiological information. The proposed webAR program is also highly adaptable, performing smoothly on most mobile platforms, providing potential benefits for medical and academic communities in improving teaching experience.