Monitoring heartbeat and respiration can help estimate the sleep state throughout the night. Here, we developed a simple method for detecting the heart rate (HR) and respiratory rate (RR) based on body vibration during sleep measured using a sheet-shaped body vibrometer (SBV) placed under a mattress. Polysomnography (PSG) signals and SBV data were simultaneously recorded in 20 subjects during a 2-hour sleep. In the SBV data, intervals including amplitude saturation caused by major and minor body movements were excluded. The heartbeat and respiratory vibration components were then extracted by signal processing via principal component analysis (PCA) and filtering. Finally, the HR and RR were calculated based on the peaks in the processed signals. The algorithm used well known and straightforward techniques. Accuracy was evaluated by comparing the HR and RR values derived from SBV with those obtained from PSG signals. The absolute relative error between PSG and SBV was defined and computed under several conditions for excluding body movement intervals. Accuracies with different threshold values of amplitude saturation detection were evaluated to extract the available epochs. The absolute relative error of HR varied from 2.86 to 4.22%, and that for RR varied from 3.62 to 5.95%. The Bland-Altman plot values for HR and RR in the case of the lowest absolute relative error were −0.85 [−8.1-6.4] and −0.19 [−2.0-1.6], respectively. This study proposes a simple algorithm for detecting HR and RR using an SBV placed under a mattress. The accuracy is almost the same as in previous studies employing more complex algorithms. The proposed method allows HR and RR detection during sleep without constraint or contact, and facilitates monitoring at nighttime.