Ballistocardiogram (BCG) signal is a physiological signal that reflects the mechanical characteristics of the heart it can achieve continuous acquisition measurements without electrode binding. However, the BCG signal is weak and highly susceptible to interference, and is often submerged in noise during measurements. In order to effectively identify BCG signals, this paper proposes a BCG denoising method based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) combined with permutation entropy (PE). Firstly, the collected BCG signal is decomposed with CEEMDAN to obtain a series of intrinsic mode function (IMF) from high to low frequencies. Secondly, the value of each IMF component is calculated with PE and the threshold range of the useful signal is determined, thereby the high frequency noise and baseline drift in the signal are filtered out. The experiment results show that the amplitudefrequency characteristics of the signal after noise reduction are significantly improved, and compared with the traditional method the signaltonoise ratio is significantly improved, which proves that the proposed noise reduction method has obvious effect and can effectively restore the BCG signal characteristics.