Estimation of the Person's Position on the Bed Considering the Surrounding Environment Based on the Depth Map

Abstract

Sleep apnea syndrome (SAS) is one of the most common sleep-related diseases. SAS can reduce sleep quality and is frequently associated with lifestyle-related diseases. Many individuals are unaware that they have this disease as SAS occurs during sleep. Although polysomnography (PSG) is used to diagnose SAS, it is not suitable for sleep monitoring on a daily basis as it requires hospitalization and the use of expensive wearable devices. The authors previously proposed a method for monitoring breathing during sleep using a depth camera in a non-contact and non-constrained manner. However, the time spent by the subject in the correct position could not be estimated because objects moving within the camera's field of view could be erroneously identified as persons. In this study, we attempt to separate beds from other room areas and identify multiple person-like moving objects within the beds using distance information from a depth camera. Consequently, we show that it is possible to estimate a person's position and respiration without interference from the surrounding environment and that the accuracy of these estimations can be improved with respect to that of the conventional method.