Review of ECG data feature processing and classification

According to statistics, about one-third of the world's deaths are caused by cardiovascular diseases, which have a significant health impact on modern young people. Therefore, the most critical issues in the medical field are the prevention and diagnosis of heart system diseases. Electrocardiogram (ECG) is currently one of the most common diagnostic techniques for cardiovascular diseases. This article reviews some denoising methods of ECG signals, including traditional denoising methods, wavelet transform denoising methods, based on FIR Denoising method, and elaborates the classification technology and improvement strategies of related ECG features, such as Random Forest(RF), Back Propagation(BP), and analyzes the advantages and disadvantages of various algorithms. Finally, all the preprocessing algorithms and classification methods of ECG are summarized, and future development has prospected.