Classification Model of Heart Sounds in Pulmonary Hypertension Based on Time-Frequency Fusion Features
Pulmonary hypertension associated with congenital heart disease has a high mortality rate,and early screening and identification of it is particularly important for cure.At present,diagnosis is made by right heart catheterization,which is an inva-sive examination,it is not easy to use in screening,and has high risk and high cost.Therefore,it is urgent to study a non-invasive and convenient method for identification.In this paper,a time-frequency fusion heart sound classification model is established.First,the heart sound signal is preprocessed,then the signal is converted,and the dynamic time-frequency characteristics are ob-tained by using the fusion filter bank.Finally,the obtained fusion feature parameters are input into the TabPFN network for clas-sification and recognition.Experimental results indicate that the algorithm has average accuracy,precision,sensitivity,specificity,and F1 scores of 92.21％,92.15％,92.15％,96.11％,and 92.14％respectively in normal,CHD-PAH,and CHD.It is important for the early screening and identification of pulmonary hypertension associated with congenital heart disease.
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