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Sensors 2017, 17(6), 1342; doi:10.3390/s17061342

Recognizing Bedside Events Using Thermal and Ultrasonic Readings

1
UiT—The Arctic University of Norway, 8505 Narvik, Norway
2
UiO—University of Oslo, 0373 Oslo, Norway
*
Author to whom correspondence should be addressed.
Academic Editors: Pino Caballero-Gil and Alexis Quesada-Arencibia
Received: 27 April 2017 / Revised: 24 May 2017 / Accepted: 6 June 2017 / Published: 9 June 2017
(This article belongs to the Special Issue Selected Papers from UCAmI 2016)
View Full-Text   |   Download PDF [2354 KB, uploaded 9 June 2017]   |  

Abstract

Falls in homes of the elderly, in residential care facilities and in hospitals commonly occur in close proximity to the bed. Most approaches for recognizing falls use cameras, which challenge privacy, or sensor devices attached to the bed or the body to recognize bedside events and bedside falls. We use data collected from a ceiling mounted 80 × 60 thermal array combined with an ultrasonic sensor device. This approach makes it possible to monitor activity while preserving privacy in a non-intrusive manner. We evaluate three different approaches towards recognizing location and posture of an individual. Bedside events are recognized using a 10-second floating image rule/filter-based approach, recognizing bedside falls with 98.62% accuracy. Bed-entry and exit events are recognized with 98.66% and 96.73% accuracy, respectively. View Full-Text
Keywords: bedside event detection; fall detection; thermal array; ultrasonic sensor; artificial intelligence; classification bedside event detection; fall detection; thermal array; ultrasonic sensor; artificial intelligence; classification
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Asbjørn, D.; Jim, T. Recognizing Bedside Events Using Thermal and Ultrasonic Readings. Sensors 2017, 17, 1342.

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