Research on the risk stratified assessment model of atherosclerotic cardiovascular disease based on pulse image information fusion
Objective:To explore the application value of pulse signal parameters extracted by fusing pressure pulse wave and photoconductive pulse wave in the stratified assessment of the incidence risk of atherosclerotic cardiovascular disease(ASCVD),and to provide a new idea and method for the risk assessment of ASCVD.Methods:The radial artery pressure pulse wave and fingertip photoconductive pulse wave of different risk groups of ASCVD were collected by pressure photoelectric multi-sensor pulse detection equipment.The time-domain parameters were extracted based on the pressure pulse wave,and the hemodynamic parameters were extracted by fusing photoconductive pulse wave;Non parametric test was used to compare the time-domain parameters and hemodynamic parameters different risk groups of ASCVD;Based on different pulse signal feature combinations,the random forest(RF)algorithm was used to establish the ASCVD incidence risk hierarchical assessment model,calculate the accuracy,precision,recall and F1 score of the model,and comprehensively compare the performance of different models.Results:The time domain parameters T,T1,T4,T5,H3/H1,H4/H1,T1/T,T4/T,W1,W2,W1/T,W2/T and hemodynamic parameters R,L,C,Pm of ASCVD with different risk stratification were significantly different(P<0.01).The RF algorithm was used to establish an ASCVD incidence risk assessment model based on the parameters of pulse signals.When the parameters of time domain and hemodynamics jointly participate in the model construction,the performance of the model was optimal:its accuracy rate was 82.05%,the average recall rate was 80.95%,the average precision rate was 80.69%,and the average F1 score was 80.62%.Conclusion:The characteristics of pulse signals extracted from pressure pulse wave and photoconductive pulse wave can reflect certain cardiovascular information;Pulse diagnosis and detection technology based on multi-source information can be used to obtain richer cardiovascular information and improve the performance of the risk stratification model of ASCVD,and pulse diagnosis detection technology based on multi-source information fusion is promising provide new tools for risk assessment and monitoring of the incidence of ASCVD.