Title :
A study of automatic classification of sleeping position by a pressure-sensitive sensor
Author :
Aya Mineharu;Noriaki Kuwahara;Kazunari Morimoto
Author_Institution :
Graduate School of Science and Technology, Kyoto Institute of Technology, Japan
fDate :
6/1/2015 12:00:00 AM
Abstract :
Currently in care facilities, a fall preventive movement sensor is often used to prevent falls of care receivers during the night‥ But the current sensors are usually designed to detect the motion of care receivers´ getting out of bed. Therefore, there are cases where the care receiver has already fallen from the bed by the time the sensor reacted to the movement. It is a common knowledge that a person frequently changes position while sleeping. In this research, we focus on the frequency of sleeping position changes, and aim to realize a method for precise prediction of care receivers´ attempt to get out of bed sufficiently before the actual action. We employed the automatic classification method of sleeping position in the pressure-sensitive sensor, with consideration to privacy of the research subjects, and identified nine types of sleeping position that are common, with 77.1% of accuracy. This result is reported in this paper.
Keywords :
"Receivers","Support vector machines","Libraries","Sensors","Feature extraction","Dementia","Turning"
Conference_Titel :
Informatics, Electronics & Vision (ICIEV), 2015 International Conference on
DOI :
10.1109/ICIEV.2015.7334059