In order to solve the problem that the existing electrocardiogram（ECG）denoising methods are difficult to accurately separate the overlapped myoelectricity interference and extract “clean” ECG, this paper proposes a method of using cardiac cycle and empirical mode decomposition to denoise the noisy ECG signal. Firstly, empirical mode decomposition is used to decompose the noisy ECG signal, and then the intrinsic modal function components of the signal are determined to be noise or useful signal by cardiac cycle. Finally, the intrinsic modal function components of the useful signal are reconstructed to be ECG signal. For validating the proposed method, the dynamic simulation model of ECG signal is used to evaluate the denoising effect of the method under different parameters of noise; and three groups of real noisy ECG are constructed by selecting baseline drift signal bw, myoelectricity interference signal ma and ECG105, 107 and 123 in MIT-BIH database, respectively. Both the evaluation and experimental results show that the method can remove the myoelectricity interference and baseline drift in ECG at the same time, and the denoising effect is better than the usual empirical method.