Publication result detail

IN-BED POSTURE CLASSIFICATION

HUSÁK, M.

Original Title

IN-BED POSTURE CLASSIFICATION

English Title

IN-BED POSTURE CLASSIFICATION

Type

Paper in proceedings outside WoS and Scopus

Original Abstract

Our work aims to create a widely applicable platform that combines the measurement of in-bed position with another’s negative states. The mentioned data are multimodal. Therefore, we used the machine learning (ML) method to obtain the properties.

English abstract

Our work aims to create a widely applicable platform that combines the measurement of in-bed position with another’s negative states. The mentioned data are multimodal. Therefore, we used the machine learning (ML) method to obtain the properties.

Keywords

Decubitus, Matrass, Machine Learning, Body posture classification

Key words in English

Decubitus, Matrass, Machine Learning, Body posture classification

Authors

HUSÁK, M.

RIV year

2021

Released

27.04.2021

Publisher

Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních

Location

Brno

ISBN

978-80-214-5942-7

Book

STUDENT EEICT 2021

Edition

1

URL

https://www.fekt.vut.cz/conf/EEICT/archiv/sborniky/EEICT_2021_sbornik_1.pdf

BibTex

@inproceedings{BUT171452,
  author="Michal {Husák}",
  title="IN-BED POSTURE CLASSIFICATION",
  booktitle="STUDENT EEICT 2021",
  year="2021",
  series="1",
  number="27",
  publisher="Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních",
  address="Brno",
  isbn="978-80-214-5942-7",
  url="https://www.fekt.vut.cz/conf/EEICT/archiv/sborniky/EEICT_2021_sbornik_1.pdf"
}