The invention relates to an identity recognition method based on ECG dynamic self-updating samples, and belongs to the technical field of biological feature identity recognition. The identity recognition method is used for recognizing and verifying personal identity information by collecting personal ECG signals. The identity recognition method based on the ECG dynamic self-updating samples is characterized in that first, cardiac cycle signals are obtained in a segmented mode through the R wave positions of the personal ECG signals; then, discrete cosine transform is used for extracting feature vectors; afterwards, a two-layer decision classifier is used for conducting personal identity recognition; finally, the identity information of the input personal EGC signals is judged, feedback is carried out according to the successfully recognized samples, a sample library is updated periodically, and it is guaranteed that the algorithm can operate normally and effectively for a long time. The algorithm comprises four modules, namely a preprocessing and feature vector extracting module, a training and learning module, a matching recognition module and a sample evaluation updating module.