Research on Heart Rate Signal Recognition Based on Deep Learning

As people’s living standards continue to improve, Cardiovascular disease has become one of the major diseases that pose a threat to human health. As one of the biological electrical signals produced by the human body, electrocardiogram (ECG) signals can intuitively reflect the health status of the heart, which is of great significance for the prevention and detection of cardiovascular diseases. This design is based on deep learning to identify abnormal heart rate signals and normal heart rate signals. The dataset comes from the public MIT-BIH dataset, and a time-frequency convolutional neural network is used to train the dataset. Compared with traditional long short-term memory networks, it has the characteristics of high recognition accuracy and fast convergence speed, which is of certain positive significance for related clinical applications.