In-Bed Posture Classification
but.event.date | 27.04.2021 | cs |
but.event.title | STUDENT EEICT 2021 | cs |
dc.contributor.author | Husák, Michal | |
dc.date.accessioned | 2021-07-21T07:07:00Z | |
dc.date.available | 2021-07-21T07:07:00Z | |
dc.date.issued | 2021 | cs |
dc.description.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. | en |
dc.format | text | cs |
dc.format.extent | 410-414 | cs |
dc.format.mimetype | application/pdf | en |
dc.identifier.citation | Proceedings I of the 27st Conference STUDENT EEICT 2021: General papers. s. 410-414. ISBN 978-80-214-5942-7 | cs |
dc.identifier.isbn | 978-80-214-5942-7 | |
dc.identifier.uri | http://hdl.handle.net/11012/200791 | |
dc.language.iso | en | cs |
dc.publisher | Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií | cs |
dc.relation.ispartof | Proceedings I of the 27st Conference STUDENT EEICT 2021: General papers | en |
dc.relation.uri | https://conf.feec.vutbr.cz/eeict/index/pages/view/ke_stazeni | cs |
dc.rights | © Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií | cs |
dc.rights.access | openAccess | en |
dc.subject | Decubitus | en |
dc.subject | Matrass | en |
dc.subject | Machine Learning | en |
dc.subject | Body posture classification | en |
dc.title | In-Bed Posture Classification | en |
dc.type.driver | conferenceObject | en |
dc.type.status | Peer-reviewed | en |
dc.type.version | publishedVersion | en |
eprints.affiliatedInstitution.department | Fakulta elektrotechniky a komunikačních technologií | cs |
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