ECG signal detection is an important measure to prevent cardiovascular diseases.The accurate detection of QRS wave is not only a key step in ECG signal processing,but also plays an important role in heart rate calculation and abnormal situation analysis.In order to solve the problem of poor signal quality or abnormal rhythm waveforms in dynamic ECG signals,which results in low accuracy of commonly used QRS wave detection methods,therefore this paper proposes a new QRS wave detection based on our proposed algorithm.The a lgorithm is based on the Pix2Pix network.The Generative network adopts the U-Net structure,the Discriminant network uses the Patch-GAN idea,and makes full use of the jump connection structure of the U-Net structure to realize the mapping of ECG data to R wave peak position data,and improve the signal-to-noise ratio of the input signal by denoising and reorganizing the original signal.Using 2000groups of single-lead ECG signals about ICBEB dynamic ECG database for algorithm verification,comparing with the other two algorithms,the results show that the accuracy rate of QRS wave detection algorithm based on our proposed algorithm reaches 99.13%,which is significantly better than the other two algorithms.Our algorithm also gets the best results on Se and +P criteria,which shows the effectiveness of the algorithm in this paper.