For the reliable acquisition of mixed signals and the effective separation and recognition of physiological parameters in a non-contact sleep monitoring system, a piezoelectric film sensor is used to obtain the pressure signal of the human body in the sleep state. Meanwhile, a charge amplification circuit and a signal conditioning circuit are adopted to collect the pressure signal in real time. During signal processing, empirical wavelet transform is employed to separate single modal components, such as the BallistoCardioGram (BCG) signal and the respiratory signal. Then, the K-means algorithm is used to cluster different types of peaks in the BCG signal so that the heart rate can be calculated through the average heartbeat cycle. The experimental results show that the designed monitoring system has strong adaptability and it can extract respiratory and heartbeat signals.