Abstract
This paper presents a sensor system that predicts behavior patterns that occur when a patient leaves a bed. We originally developed plate-shaped sensors using piezoelectric elements. Existing sensors such as clip sensors and mat sensors require that patients be restrained. The features of our sensors are that they require no power supply or patient restraint for privacy problems. Moreover, we devel- oped machine-learning algorithms to predict behavior patterns without setting thresholds. We evaluated our system for ten subjects at an experimental environment constructed in reference to a clinical site. The mean recognition accuracy was 75.0% for seven behavior patterns. Especially, the recognition accuracies of lateral sitting and terminal sitting were 90.0% and 96.7%, respectively. We consider that these capabili- ties are useful for bed-leaving prediction in practical use.
Highlights
According to the National Population Census 2010 in Japan, the aging rate of the country is 23.1% [1]
Results show that our method predicted seven behavior patterns related to bed-leaving, especially for longitudinal sitting and terminal sitting
Output signal patterns are changed according to the transition of longitudinal sitting after sleeping, lateral sitting after turning the body to the exit, and terminal sitting, which is the situation immediately before leaving the bed
Summary
According to the National Population Census 2010 in Japan, the aging rate of the country is 23.1% [1]. Uezono et al proposed a large-scale monitoring system for detecting bed-leaving behavior patterns using 96 strain gauges assigned for a reticular pattern [16]. These large-scale sensor systems can realize higher accuracy and more stable detection than low-cost sensors, such as clip sensors or mat sensors, can. Hatsukari et al developed a bed-leaving detection system using strain gauges installed inside of actuators to obtain weight changes of a person on a bed [17]. They embedded sensors and a controller to Paramount beds as a new product of their company Paramount Bed Co. Ltd. Results show that our method predicted seven behavior patterns related to bed-leaving, especially for longitudinal sitting and terminal sitting
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