2017 Volume 55Annual Issue Proc Pages 552-553
This paper presents an automatic sleep quality assessment method based on an unobtrusive sleep monitoring system, which comprises mainly of a bed sensor monitoring heart rate, respiratory rate, body movement during sleeping and leaving the bed, and a cloud system processing the daily sleep data. The data obtained during sleep are further derived to mine features and pattern of sleep so that it can be used to rate the sleep from a predefined scale. Six subjects were employed to evaluate the validity of the proposed sleep quality assessment method. Experimental results preliminarily show that the consistency and validity of our method comparing to the reference Pittsburgh sleep quality index (PSQI), which is a traditional sleep quality assessment method.