Posture Classification with a Bed-Monitoring System Using Radio Frequency Identification.

Aging of the population and the declining birthrate in Japan have produced severe human resource shortages in the medical and long-term care industries. Reportedly, falls account for more than 50% of all accidents in nursing homes. Recently, various bed-release sensors have become commercially available.

Development of Invisible Sensors and a Machine-Learning-Based Recognition System Used for Early Prediction of Discontinuous Bed-Leaving Behavior Patterns.

This paper presents a novel bed-leaving sensor system for real-time recognition of bed-leaving behavior patterns. The proposed system comprises five pad sensors installed on a bed, a rail sensor inserted in a safety rail, and a behavior pattern recognizer based on machine learning. The linear characteristic between loads and output was obtained from a load test to evaluate sensor output characteristics.