Cargando…

Predicting balance impairments in older adults: a wavelet-based center of pressure classification approach

BACKGROUND: Aging is associated with a decline in postural control and an increased risk of falls. The Center of Pressure (CoP) trajectory analysis is a commonly used method to assess balance. In this study, we proposed a new method to identify balance impairments in older adults by analyzing their...

Descripción completa

Detalles Bibliográficos
Autores principales: Jafari, Hedyeh, Gustafsson, Thomas, Nyberg, Lars, Röijezon, Ulrik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10463618/
https://www.ncbi.nlm.nih.gov/pubmed/37608334
http://dx.doi.org/10.1186/s12938-023-01146-3
_version_ 1785098273655095296
author Jafari, Hedyeh
Gustafsson, Thomas
Nyberg, Lars
Röijezon, Ulrik
author_facet Jafari, Hedyeh
Gustafsson, Thomas
Nyberg, Lars
Röijezon, Ulrik
author_sort Jafari, Hedyeh
collection PubMed
description BACKGROUND: Aging is associated with a decline in postural control and an increased risk of falls. The Center of Pressure (CoP) trajectory analysis is a commonly used method to assess balance. In this study, we proposed a new method to identify balance impairments in older adults by analyzing their CoP trajectory frequency components, sensory inputs, reaction time, motor functions, and Fall-related Concerns (FrC). METHODS: The study includes 45 older adults aged [Formula: see text] years who were assessed for sensory and motor functions. FrC and postural control in a quiet stance with open and closed eyes on stable and unstable surfaces. A Discrete Wavelet Transform (DWT) was used to detect features in frequency scales, followed by the K-means algorithm to detect different clusters. The multinomial logistic model was used to identify and predict the association of each group with the sensorimotor tests and FrC. RESULTS: The study results showed that by DWT, three distinct groups of subjects could be revealed. Group 2 exhibited the broadest use of frequency scales, less decline in sensorimotor functions, and lowest FrC. The study also found that a decline in sensorimotor functions and fall-related concern may cause individuals to rely on either very low-frequency scales (group 1) or higher-frequency scales (group 3) and that those who use lower-frequency scales (group 1) can manage their balance more successfully than group 3. CONCLUSIONS: Our study provides a new, cost-effective method for detecting balance impairments in older adults. This method can be used to identify people at risk and develop interventions and rehabilitation strategies to prevent falls in this population.
format Online
Article
Text
id pubmed-10463618
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-104636182023-08-30 Predicting balance impairments in older adults: a wavelet-based center of pressure classification approach Jafari, Hedyeh Gustafsson, Thomas Nyberg, Lars Röijezon, Ulrik Biomed Eng Online Research BACKGROUND: Aging is associated with a decline in postural control and an increased risk of falls. The Center of Pressure (CoP) trajectory analysis is a commonly used method to assess balance. In this study, we proposed a new method to identify balance impairments in older adults by analyzing their CoP trajectory frequency components, sensory inputs, reaction time, motor functions, and Fall-related Concerns (FrC). METHODS: The study includes 45 older adults aged [Formula: see text] years who were assessed for sensory and motor functions. FrC and postural control in a quiet stance with open and closed eyes on stable and unstable surfaces. A Discrete Wavelet Transform (DWT) was used to detect features in frequency scales, followed by the K-means algorithm to detect different clusters. The multinomial logistic model was used to identify and predict the association of each group with the sensorimotor tests and FrC. RESULTS: The study results showed that by DWT, three distinct groups of subjects could be revealed. Group 2 exhibited the broadest use of frequency scales, less decline in sensorimotor functions, and lowest FrC. The study also found that a decline in sensorimotor functions and fall-related concern may cause individuals to rely on either very low-frequency scales (group 1) or higher-frequency scales (group 3) and that those who use lower-frequency scales (group 1) can manage their balance more successfully than group 3. CONCLUSIONS: Our study provides a new, cost-effective method for detecting balance impairments in older adults. This method can be used to identify people at risk and develop interventions and rehabilitation strategies to prevent falls in this population. BioMed Central 2023-08-22 /pmc/articles/PMC10463618/ /pubmed/37608334 http://dx.doi.org/10.1186/s12938-023-01146-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Jafari, Hedyeh
Gustafsson, Thomas
Nyberg, Lars
Röijezon, Ulrik
Predicting balance impairments in older adults: a wavelet-based center of pressure classification approach
title Predicting balance impairments in older adults: a wavelet-based center of pressure classification approach
title_full Predicting balance impairments in older adults: a wavelet-based center of pressure classification approach
title_fullStr Predicting balance impairments in older adults: a wavelet-based center of pressure classification approach
title_full_unstemmed Predicting balance impairments in older adults: a wavelet-based center of pressure classification approach
title_short Predicting balance impairments in older adults: a wavelet-based center of pressure classification approach
title_sort predicting balance impairments in older adults: a wavelet-based center of pressure classification approach
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10463618/
https://www.ncbi.nlm.nih.gov/pubmed/37608334
http://dx.doi.org/10.1186/s12938-023-01146-3
work_keys_str_mv AT jafarihedyeh predictingbalanceimpairmentsinolderadultsawaveletbasedcenterofpressureclassificationapproach
AT gustafssonthomas predictingbalanceimpairmentsinolderadultsawaveletbasedcenterofpressureclassificationapproach
AT nyberglars predictingbalanceimpairmentsinolderadultsawaveletbasedcenterofpressureclassificationapproach
AT roijezonulrik predictingbalanceimpairmentsinolderadultsawaveletbasedcenterofpressureclassificationapproach