Original title: In-Bed Posture Classification
Authors: Husák, Michal
Document type: Papers
Language: eng
Publisher: Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
Abstract: The growing trend of the population age contributes to the accumulation of patients insocial facilities and in-home care, which leads to growing chronic diseases. Modern systems try toimprove the effectiveness of health care interventions. Our work aims to create a widely applicableplatform that combines the measurement of in-bed position with another’s negative states. All thesephysical influences are mainly the cause of chronic tissue damage (pressure ulcers). Processing ofthe pressure distribution on the bed is a more dimension problem. The mentioned data are multimodal.Therefore, we used the machine learning (ML) method to obtain the properties.
Keywords: Body posture classification; Decubitus; Machine Learning; Matrass
Host item entry: Proceedings I of the 27st Conference STUDENT EEICT 2021: General papers, ISBN 978-80-214-5942-7

Institution: Brno University of Technology (web)
Document availability information: Fulltext is available in the Brno University of Technology Digital Library.
Original record: http://hdl.handle.net/11012/200791

Permalink: http://www.nusl.cz/ntk/nusl-447836


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