Low cost and batteryless sensor-enabled radio frequency identification tag based approaches to identify patient bed entry and exit posture transitions.
INTRODUCTION
Falls in hospitals and residential care facilities commonly occur near the bed. The aim of this study was to investigate the accuracy of a continuously wearable, batteryless, low power and low cost monitoring device (Wearable Wireless Identification and Sensing Platform) with a single kinematic sensor capable of real-time monitoring to automatically detect bed entry and exit events.


MATERIALS AND METHODS
Three dimensional acceleration readings and the strength of the transmitted signal from the WISP was interpreted to identify bed exit events and sensitivity, specificity and Receiving Operator Curves (ROC) were determined.


RESULTS
The sensor located over sternum method performed best with sensitivity and specificity values of 92.8% and 97.5% respectively for detecting bed entry and values of 90.4% and 93.80% respectively for bed exit. On the other hand, the sensor-on-mattress algorithm achieved sensitivity and specificity values of 84.2% and 97.4% respectively for bed entry and 79% and 97.4% for bed exit detection.


CONCLUSION
The WISP located over the sternum method is the preferred method to detect bed entry and exit. However, further work in frail older people is required to confirm the performance of this method.
['Ranasinghe|D C|DC|', 'Shinmoto Torres|R L|RL|', 'Hill|K|K|', 'Visvanathan|R|R|']
D000054:Acceleration D000058:Accidental Falls D000368:Aged D000465:Algorithms D001513:Beds D003365:Costs and Cost Analysis D004867:Equipment Design D006801:Humans D004856:Postural Balance D012372:ROC Curve D057233:Radio Frequency Identification Device
Radio frequency identification Postural transitions Bed exit alarm Elderly Wearable sensor