Cargando…
Model of the Performance Based on Artificial Intelligence–Fuzzy Logic Description of Physical Activity
FEATURED APPLICATION: Potential applications of the work are systems for objective artificial-intelligent performance assessment in healthy individuals (including athletes) and patients with various injuries and conditions, including within the eHealth paradigm, including future wearable devices (e....
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9918994/ https://www.ncbi.nlm.nih.gov/pubmed/36772159 http://dx.doi.org/10.3390/s23031117 |
_version_ | 1784886714078068736 |
---|---|
author | Szulc, Adam Prokopowicz, Piotr Buśko, Krzysztof Mikołajewski, Dariusz |
author_facet | Szulc, Adam Prokopowicz, Piotr Buśko, Krzysztof Mikołajewski, Dariusz |
author_sort | Szulc, Adam |
collection | PubMed |
description | FEATURED APPLICATION: Potential applications of the work are systems for objective artificial-intelligent performance assessment in healthy individuals (including athletes) and patients with various injuries and conditions, including within the eHealth paradigm, including future wearable devices (e.g., e-shoes). ABSTRACT: The aim of the study was to build a fuzzy model of lower limb peak torque in an isokinetic mode. The study involved 93 male participants (28 male deaf soccer players, 19 hearing soccer players and 46 deaf untraining male). A fuzzy computational model of different levels of physical activity with a focus on the lower limbs was constructed. The proposed fuzzy model assessing lower limb peak torque in an isokinetic mode demonstrated its effectiveness. The novelty of our research lies in the use of hierarchical fuzzy logic to extract computational rules from data provided explicitly and then to determine the corresponding physiological and pathological mechanisms. The contribution of our research lies in complementing the methods for describing physiology, pathology and rehabilitation with fuzzy parameters, including the so-called dynamic norm embedded in the model. |
format | Online Article Text |
id | pubmed-9918994 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-99189942023-02-12 Model of the Performance Based on Artificial Intelligence–Fuzzy Logic Description of Physical Activity Szulc, Adam Prokopowicz, Piotr Buśko, Krzysztof Mikołajewski, Dariusz Sensors (Basel) Article FEATURED APPLICATION: Potential applications of the work are systems for objective artificial-intelligent performance assessment in healthy individuals (including athletes) and patients with various injuries and conditions, including within the eHealth paradigm, including future wearable devices (e.g., e-shoes). ABSTRACT: The aim of the study was to build a fuzzy model of lower limb peak torque in an isokinetic mode. The study involved 93 male participants (28 male deaf soccer players, 19 hearing soccer players and 46 deaf untraining male). A fuzzy computational model of different levels of physical activity with a focus on the lower limbs was constructed. The proposed fuzzy model assessing lower limb peak torque in an isokinetic mode demonstrated its effectiveness. The novelty of our research lies in the use of hierarchical fuzzy logic to extract computational rules from data provided explicitly and then to determine the corresponding physiological and pathological mechanisms. The contribution of our research lies in complementing the methods for describing physiology, pathology and rehabilitation with fuzzy parameters, including the so-called dynamic norm embedded in the model. MDPI 2023-01-18 /pmc/articles/PMC9918994/ /pubmed/36772159 http://dx.doi.org/10.3390/s23031117 Text en © 2023 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 Szulc, Adam Prokopowicz, Piotr Buśko, Krzysztof Mikołajewski, Dariusz Model of the Performance Based on Artificial Intelligence–Fuzzy Logic Description of Physical Activity |
title | Model of the Performance Based on Artificial Intelligence–Fuzzy Logic Description of Physical Activity |
title_full | Model of the Performance Based on Artificial Intelligence–Fuzzy Logic Description of Physical Activity |
title_fullStr | Model of the Performance Based on Artificial Intelligence–Fuzzy Logic Description of Physical Activity |
title_full_unstemmed | Model of the Performance Based on Artificial Intelligence–Fuzzy Logic Description of Physical Activity |
title_short | Model of the Performance Based on Artificial Intelligence–Fuzzy Logic Description of Physical Activity |
title_sort | model of the performance based on artificial intelligence–fuzzy logic description of physical activity |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9918994/ https://www.ncbi.nlm.nih.gov/pubmed/36772159 http://dx.doi.org/10.3390/s23031117 |
work_keys_str_mv | AT szulcadam modeloftheperformancebasedonartificialintelligencefuzzylogicdescriptionofphysicalactivity AT prokopowiczpiotr modeloftheperformancebasedonartificialintelligencefuzzylogicdescriptionofphysicalactivity AT buskokrzysztof modeloftheperformancebasedonartificialintelligencefuzzylogicdescriptionofphysicalactivity AT mikołajewskidariusz modeloftheperformancebasedonartificialintelligencefuzzylogicdescriptionofphysicalactivity |