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Application of Fuzzy and Rough Logic to Posture Recognition in Fall Detection System

Considering that the population is aging rapidly, the demand for technology for aging-at-home, which can provide reliable, unobtrusive monitoring of human activity, is expected to expand. This research focuses on improving the solution of the posture detection problem, which is a part of fall detect...

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Autores principales: Pȩkala, Barbara, Mroczek, Teresa, Gil, Dorota, Kepski, Michal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8877837/
https://www.ncbi.nlm.nih.gov/pubmed/35214508
http://dx.doi.org/10.3390/s22041602
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author Pȩkala, Barbara
Mroczek, Teresa
Gil, Dorota
Kepski, Michal
author_facet Pȩkala, Barbara
Mroczek, Teresa
Gil, Dorota
Kepski, Michal
author_sort Pȩkala, Barbara
collection PubMed
description Considering that the population is aging rapidly, the demand for technology for aging-at-home, which can provide reliable, unobtrusive monitoring of human activity, is expected to expand. This research focuses on improving the solution of the posture detection problem, which is a part of fall detection system. Fall detection, using depth maps obtained by the Microsoft Kinect sensor, is a two-stage method. We concentrate on the first stage of the system, that is, pose recognition from a depth map. For lying pose detection, a new hybrid FRSystem is proposed. In the system, two rule sets are investigated, the first one created based on a domain knowledge and the second induced based on the rough set theory. Additionally, two inference aggregation approaches are considered with and without the knowledge measure. The results indicate that the new axiomatic definition of knowledge measures, which we propose has a positive impact on the effectiveness of inference and the rule induction method reducing the number of rules in a set maintains it.
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spelling pubmed-88778372022-02-26 Application of Fuzzy and Rough Logic to Posture Recognition in Fall Detection System Pȩkala, Barbara Mroczek, Teresa Gil, Dorota Kepski, Michal Sensors (Basel) Article Considering that the population is aging rapidly, the demand for technology for aging-at-home, which can provide reliable, unobtrusive monitoring of human activity, is expected to expand. This research focuses on improving the solution of the posture detection problem, which is a part of fall detection system. Fall detection, using depth maps obtained by the Microsoft Kinect sensor, is a two-stage method. We concentrate on the first stage of the system, that is, pose recognition from a depth map. For lying pose detection, a new hybrid FRSystem is proposed. In the system, two rule sets are investigated, the first one created based on a domain knowledge and the second induced based on the rough set theory. Additionally, two inference aggregation approaches are considered with and without the knowledge measure. The results indicate that the new axiomatic definition of knowledge measures, which we propose has a positive impact on the effectiveness of inference and the rule induction method reducing the number of rules in a set maintains it. MDPI 2022-02-18 /pmc/articles/PMC8877837/ /pubmed/35214508 http://dx.doi.org/10.3390/s22041602 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Pȩkala, Barbara
Mroczek, Teresa
Gil, Dorota
Kepski, Michal
Application of Fuzzy and Rough Logic to Posture Recognition in Fall Detection System
title Application of Fuzzy and Rough Logic to Posture Recognition in Fall Detection System
title_full Application of Fuzzy and Rough Logic to Posture Recognition in Fall Detection System
title_fullStr Application of Fuzzy and Rough Logic to Posture Recognition in Fall Detection System
title_full_unstemmed Application of Fuzzy and Rough Logic to Posture Recognition in Fall Detection System
title_short Application of Fuzzy and Rough Logic to Posture Recognition in Fall Detection System
title_sort application of fuzzy and rough logic to posture recognition in fall detection system
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8877837/
https://www.ncbi.nlm.nih.gov/pubmed/35214508
http://dx.doi.org/10.3390/s22041602
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