Effectiveness of a Batteryless and Wireless Wearable Sensor System for Identifying Bed and Chair Exits in Healthy Older PeopleReportar como inadecuado




Effectiveness of a Batteryless and Wireless Wearable Sensor System for Identifying Bed and Chair Exits in Healthy Older People - Descarga este documento en PDF. Documentación en PDF para descargar gratis. Disponible también para leer online.

1

Auto-ID Lab, The University of Adelaide, North Terrace, Adelaide SA 5005, Australia

2

Aged and Extended Care Services, The Queen Elizabeth Hospital, Woodville South SA 5011, Australia

3

Adelaide Geriatrics Training and Research with Aged Care GTRAC Centre, The University of Adelaide, North Terrace, Adelaide SA 5005, Australia

4

Australian Centre for Visual Technologies, The University of Adelaide, North Terrace, Adelaide SA 5005, Australia





*

Author to whom correspondence should be addressed.



Academic Editor: Panicos Kyriacou

Abstract Aging populations are increasing worldwide and strategies to minimize the impact of falls on older people need to be examined. Falls in hospitals are common and current hospital technological implementations use localized sensors on beds and chairs to alert caregivers of unsupervised patient ambulations; however, such systems have high false alarm rates. We investigate the recognition of bed and chair exits in real-time using a wireless wearable sensor worn by healthy older volunteers. Fourteen healthy older participants joined in supervised trials. They wore a batteryless, lightweight and wireless sensor over their attire and performed a set of broadly scripted activities. We developed a movement monitoring approach for the recognition of bed and chair exits based on a machine learning activity predictor. We investigated the effectiveness of our approach in generating bed and chair exit alerts in two possible clinical deployments Room 1 and Room 2. The system obtained recall results above 93% Room 2 and 94% Room 1 for bed and chair exits, respectively. Precision was >78% and 67%, respectively, while F-score was >84% and 77% for bed and chair exits, respectively. This system has potential for real-time monitoring but further research in the final target population of older people is necessary. View Full-Text

Keywords: fall prevention; bed exits; chair exits; weighted conditional random fields; older people fall prevention; bed exits; chair exits; weighted conditional random fields; older people





Autor: Roberto Luis Shinmoto Torres 1,* , Renuka Visvanathan 2,3, Stephen Hoskins 2, Anton van den Hengel 4 and Damith C. Ranasinghe 1

Fuente: http://mdpi.com/



DESCARGAR PDF




Documentos relacionados