Development of Under Bed Mounted Obrid-Sensor for Bed-Exit Detection

In an aging society, accidents involving the elderly constitute a significant social issue. Constant supervision by caregivers, regardless of day or night, is essential for accident prevention, but this leads to an increased burden on caregivers, posing a serious challenge. Against this backdrop, there is a demand for the development of bed-exit detection systems as a monitoring solution for the elderly. Previous research has proposed a system capable of detecting a person's bed-exit while preserving privacy using a sensor called Obrid-Sensor. However, it presented practical challenges. Thus, this study proposes a bed-exit detection method that can adapt to actual environmental changes. The proposed method installs the sensor with infrared LEDs and IR filters under the caregiving bed. Moreover, we extracted the features of the target by applying the inter-frame difference methods to the brightness waveforms obtained. Accordingly, it becomes feasible to robustly detect bed-exit events while minimizing the influence of natural and artificial lighting. To evaluate the effectiveness of the proposed method, verification experiments were conducted against diverse background changes in actual environments. The results revealed that the bed-exit detection rate reached 100%, confirming the practicality of the proposed method, regardless of changes in the real environment or nighttime conditions. Additionally, the false-positive rate was restrained to 10.7% or less against factors potentially leading to misidentification, ensuring a reduction in erroneous detections. These findings suggest that the proposed method can be effectively utilized as a monitoring system for the elderly in actual environments.