Sleep monitoring has drawn increasingly attention as the quality and quantity of the sleep are important for maintaining a person’s health and well-being. For example, inadequate and irregular sleep are usually associated with serious health problems such as fatigue, depression and cardiovascular disease. Traditional sleep monitor- ing systems, such as PSG, involve wearable sensors with profes- sional installations, and thus are limited to clinical usage. Recent work in using smartphone sensors for sleep monitoring can detect several events related to sleep, such as body movement, cough and snore. Such coarse-grained sleep monitoring however is unable to detect the breathing rate which is a vital sign and health indicator. Thiswork presents a fine-grained sleepmonitoring systemwhich is capable of detecting the breathing rate by leveraging smartphones. Our systemexploits the readily available smartphone earphone that placed close to the user to capture the breath sound reliably. Given the captured acoustic signal, our system performs noise reduction to remove environmental noise and then identifies the breathing rate based on the signal envelope detection. Our experimental eval- uation of six subjects over six months time period demonstrates that the breathing rate monitoring is highly accurate and robust un- der various environments. This strongly indicates the feasibility of using the smartphone and its earphone to perform continuous and noninvasive fine-grained sleep monitoring.
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