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- W3204843295 abstract "The world is expecting an aging population and shortage of healthcare professionals. This poses the problem of providing a safe and dignified life for the elderly. Technological solutions involving cameras can contribute to safety, comfort and efficient emergency responses, but they are invasive of privacy. We use ’Griddy’, a prototype with a Panasonic Grid-EYE, a low-resolution infrared thermopile array sensor, which offers more privacy. Mounted over a bed, it can determine if the user is on the bed or not without human interaction. For this purpose, two datasets were captured, one (480 images) under constant conditions, and a second one (200 images) under different variations such as use of a duvet, sleeping with a pet, or increased room temperature. We test three machine learning algorithms: Support Vector Machines (SVM), k-Nearest Neighbors (k-NN) and Neural Network (NN). With 10-fold cross validation, the highest accuracy in the main dataset is for both SVM and k-NN (99%). The results with variable data show a lower reliability under certain circumstances, highlighting the need of extra work to meet the challenge of variations in the environment." @default.
- W3204843295 created "2021-10-11" @default.
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- W3204843295 date "2021-09-26" @default.
- W3204843295 modified "2023-10-18" @default.
- W3204843295 title "In-Bed Person Monitoring Using Thermal Infrared Sensors" @default.
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- W3204843295 doi "https://doi.org/10.15439/2021f15" @default.
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