Abstract: In recently, cardiovascular disease has become the common disease. With the development of machine learning and big data technology, the processing ability of electrocardiogram (ECG) signal has been greatly improved through new computer technology, which made cardiovascular disease (CVD) auxiliary diagnosis technology getting the new improvement. The application of machine learning in ECG processing, especially in the auxiliary diagnosis of diseases are discussed. Firstly, the regular signal preprocessing means are introduced. After that, the application of assisted diagnosis methods based on feature extraction and fuzzy classification is discussed. Secondly, the application of the auxiliary diagnosis in CVD is further summarized. Finally, the advantages and disadvantages of the two methods are summarized. And a design of auxiliary diagnostic system compatible with the two methods is proposed, which provides a new idea for similar applied research in the future.