Bed-Leaving Detection Using Piezoelectric Unrestrained Sensors and Its Measurement System Regarding QOL
Hirokazu Madokoro, Nobuhiro Shimoi, Kazuhito Sato · Nursing and Health · 2013
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 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 capabilities are useful for bed-leaving prediction in practical use.