Recognizing Bedside Events Using Thermal and Ultrasonic Readings
| Autor: | Torresen Jim, Danielsen Asbjørn |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Engineering
lcsh:Chemical technology Biochemistry Article Analytical Chemistry 03 medical and health sciences thermal array ultrasonic sensor 0302 clinical medicine Residential care VDP::Teknologi: 500::Medisinsk teknologi: 620 lcsh:TP1-1185 Computer vision 030212 general & internal medicine Electrical and Electronic Engineering Instrumentation Simulation business.industry bedside event detection fall detection artificial intelligence classification Atomic and Molecular Physics and Optics Ultrasonic sensor Artificial intelligence business 030217 neurology & neurosurgery VDP::Technology: 500::Medical technology: 620 |
| Zdroj: | Sensors; Volume 17; Issue 6; Pages: 1342 Sensors (Basel, Switzerland) Sensors, Vol 17, Iss 6, p 1342 (2017) |
| ISSN: | 1706-1342 1424-8220 |
| Popis: | Source at http://dx.doi.org/10.3390/s17061342 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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