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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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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. |
format | Online Article Text |
id | pubmed-8877837 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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