DocumentCode :
1766918
Title :
Bed exit prediction based on movement and posture data
Author :
Harma, Aki ; ten Kate, Warner ; Espina, Javier
Author_Institution :
Philips Res., Eindhoven, Netherlands
fYear :
2014
fDate :
1-4 June 2014
Firstpage :
165
Lastpage :
168
Abstract :
Falls in nursing homes and hospitals take often place immediately after a bed exit of a patient. An alarm signaling the exit from the bed may already be too late for staff to react. In this paper we explore the possibilities of detecting the sequences of preparatory movements before the bed exit and in this way create an early warning of the preparation of bed exit. The method is described and tested using annotated accelerometer data collected from volunteers. A plausibility assessment is also done by comparing accelerometer data from hospital patients with the output of a bed alarm system. It is demonstrated that the proposed method is able to detect a bed exit already seconds before the patient actually leaves the bed.
Keywords :
accelerometers; alarm systems; biomechanics; biomedical measurement; patient care; annotated accelerometer data; bed alarm system; bed exit prediction; bed exit preparation; early warning; falls; hospital patients; hospitals; movement data; nursing homes; patient bed exit; posture data; preparatory movements; sequence detection; Accelerometers; Detectors; Graphical models; Hidden Markov models; Hospitals; Radiofrequency identification; Sensitivity;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical and Health Informatics (BHI), 2014 IEEE-EMBS International Conference on
Conference_Location :
Valencia
Type :
conf
DOI :
10.1109/BHI.2014.6864330
Filename :
6864330
Link To Document :
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