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Recognizing Bedside Events Using Thermal and Ultrasonic Readings

Permanent link
https://hdl.handle.net/10037/11398
DOI
https://doi.org/10.3390/s17061342
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Date
2017-06-09
Type
Journal article
Tidsskriftartikkel
Peer reviewed

Author
Danielsen, Asbjørn; Tørresen, Jim
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.
Description
Source at http://dx.doi.org/10.3390/s17061342
Publisher
MDPI
Citation
Danielsen A, Tørresen J. Recognizing Bedside Events Using Thermal and Ultrasonic Readings. Sensors. 2017;17(6):1-19
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  • Artikler, rapporter og annet (datateknologi og beregningsorienterte ingeniørfag) [171]

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