Multi label abnormal heart rate detection method based on Mixup is proposed to address the high variability of electrocardiograms between different samples and the insufficient generalization ability of deep learning models.Firstly,the electrocardiogram is mixed with white noise using the Mixup method;Then,use mixed samples to train deep learning models;Finally,the experiment was conducted on the CPSC 2018 dataset,compared to Inception-ResNet-v2,MLC-CNN,STA-CRNN,the F1 scores of this method have increased by 0.014,0.031,and 0.023,respectively.
国家科技期刊平台
NSTL
万方数据
