Monitoring sleep quality and status is important to learn health condition for improvement and prevent sleep apnea. A bed-mounted seismometer system is proposed to monitor the heart and respiratory rates, and body movement and posture, during the sleep. To effectively monitor sleep status, an innovative local maxima statistics based approach and an instantaneous property based method are developed to estimate heart and respiratory rates, respectively. These methods are more robust and stable compared to previous works. Besides, algorithms for body movement and posture identification are also investigated based on instantaneous properties. A prototype system is demonstrated, showing great potentials in monitoring a person’s sleep status under different conditions.