Unrestrained sensors using piezoelectric elements for bed-leaving prediction

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 developed machine-learning algorithms to predict behavior patterns without setting thresholds. We evaluated our system for three subjects at an experimental environment constructed in reference to a clinical site. The mean recognition accuracy was 78.6% for seven behavior patterns. Especially, the recognition accuracies of lateral sitting and terminal sitting were each 94.4%. We consider that these capabilities are useful for bed-leaving prediction in practical use.