The reduction of the muscle and electrode motion artifacts in ECG using the adaptive Fourier decomposition (AFD) is investigated. This is an extension of our previous work, in which AFD is first proposed for ECG denoising and its effectiveness in filtering out the additive Gaussian white noise is tested. This paper studies the AFD-based ECG denoising method for two types of ECG noise due to the electrode movement and the muscle contraction which are common and important in practice. In addition, some rules on the selection and adjustment of the AFD decomposition level are proposed. The tests on the MIT-BIH Arrhythmia Database indicate that this AFD-based denoising scheme performs better than the Butterworth lowpass filter, the wavelet transform and the empirical mode decomposition methods for ECG denoising with the muscle movement and electrode motion artifacts.