Unconstrained detection of respiration rate and efficiency of sleep with pillow-based sensor array

An unconstrained real-time method to detect the relationship between breathing patterns and sleep efficiency (%SE) during sleep was developed using a low-cost sleep monitoring system. This system consists of an array of force sensitive resistors (FSR) sensors embedded on a pillow-sheet, wireless network devices based on low-cost ZigBee technology to digitize and transmit the pressure data to desktop computer or display devices, software to analyze and classify body movements. The characteristic breathing patterns are explained by the change of the head pressure distribution on the pillow due to the lifting and lowing of the thorax movement. We have found that the body movement frequency is different among individuals during sleep. The aim of this paper was to evaluate the quality of breathing and sleep efficiency by using the frequency of body movement during the night that were classified using a newly developed classification algorithm based on thorax movement. Here we show that quality of sleep can be characterized and distinguished by correlations of breathing rates separated by lifting and lowing of the thorax motion. The integration of this sensor system and wireless technology with computer software could make this healthcare monitoring system a commercial product valuable for point-of-care applications.