RESUMO
This paper presents the design and a first evaluation of a new monitoring system based on contactless sensors to estimate sleep quality. This sensor produces thermal signals which have been used, at first, to detect a human presence in the bed and then to estimate sleep quality. To distinguish between different sleep phases, we have used methods of signal processing in order to extract the necessary features for learning an adapted statistical model. The existing monitoring systems use sensors attached to the bed or worn by the person. We propose in this paper a system based on a passive thermal sensor which has the advantage of being fixed on the wall, thus it is easier to use and more reliable. We explain different signal processing steps and describe sleep stage recognition algorithms. We propose an adaptation of the SAX method for the thermal signal. Finally, we evaluate our system in comparison with a polysomnographic recording system in the Hospital (CHU) of Limoges.
RESUMO
This paper addresses a localization system which is based on a combination of information from two modalities: a Smart Home Person Tracking (SHPT) composed of infrared sensors and an Audio Person Tracking (APT) which uses microphones able to estimate azimuth of acoustic sources. This combination improves precision of localization compared to a standalone or separated module. The localization software facilitates the integration of both SHPT and APT systems, to display the position in real time, to record data and detect some distress situations (some kind of fall). Results on implementation show good adaptation for Smart Home environments and a robust detection.
