Detection of sleep-disordered breathing and sleep efficiency with wireless pillow-sheet sensor network

This work introduces a smart sleep care system based on pressure sensors embedded within a pillow sheet that can offer an unobtrusive method for sleep monitoring. This system consists of an array of pressure sensors, wireless network devices, and software to analyze and classify body movements. We have demonstrated this system by evaluating the quality of breathing and sleep efficiency based on detection of the frequency of head movement during the night, which are then classified using a newly developed classification algorithm. We have found that the frequency of body movement is different among individuals during sleep. Here, we have shown that the quality of sleep can be characterized and distinguished by correlations of the breathing rates separated by lifting and lowing of the thorax motion. In the sleep-disordered breathing, such as apnea, the diagnosis is based on events during which the person stops breathing for several periods during sleep. The results were compared with the gold standard measurement scheme, such as the laboratory polysomnogram (PSG), for reasonable validity in assessing sleep physiology of health and disease. We have found a high correlation coefficient between PSG and our Pillow-sheet device ( \gt0.80) for sleep efficiency and sleep latency. In summary, this pillowsheet device is effective as an alternative approach not only for determining respiration rates but also for identifying breathing patterns that can be used to identify sleep-related breathing disorders.