Nonconstrained sleep monitoring system and algorithms using air-mattress with balancing tube method

Abstract

We evaluated the performance of a bed-type sensor system using the air-mattress with balancing tube (AMBT) method to noninvasively monitor the signals of heartbeat, respiration, and events of snoring, sleep apnea and body movement of subject on the system. The proposed system consists of multiple cylindrical air cells, two sensor cells and 18 support cells, and the small physiological signals were measured by the changes in pressure difference between the sensor cells, and the dc component was removed by balancing tube that is connecting the sensor cells. Using newly developed AMBT method, heartbeat, respiration, snoring, and body movement signals were clearly measured. For the concept of a home healthcare system, two automatic processing algorithms were developed: one is to estimate the mean heart and respiration rates for every 30 s, and another one is to detect the snoring, sleep apnea, and body movement events from the measured signals. In the beat-to-beat heart rate and breath-by-breath respiration rate analyses, the correlation coefficients of the heart and respiration rates from the proposed AMBT method compared with reference methods, electrocardiogram, and respiration effort signal from piezoelectric belt, were 0.98 ( p << 0.01) and 0.96 ( p << 0.01), respectively. Sensitivity and positive predictive value (PPV) of the detection algorithm for snoring event were 93%, 96%, for sleep apnea event were 93%, 88%, and for body movement event were 86%, 100%, respectively. These findings support that ABMT method provides an accurate and reliable means to monitor heartbeat, respiration activities and the sleep events during sleep.