Classification of Center of Mass Acceleration Patterns in Older People with Knee Osteoarthritis and Fear of Falling

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dc.contributor.authorGonzález Olguín, Arturo
dc.contributor.authorRamos Rodríguez, Diego
dc.contributor.authorHigueras Córdoba, Francisco
dc.contributor.authorMartínez Rebolledo, Luis
dc.contributor.authorTaramasco, Carla
dc.contributor.authorRobles Cruz, Diego
dc.date.accessioned2023-08-10T16:34:44Z
dc.date.available2023-08-10T16:34:44Z
dc.date.issued2022-10
dc.descriptionIndexación: Scopus.es
dc.description.abstract(1) Background: The preoccupation related to the fall, also called fear of falling (FOF) by some authors is of interest in the fields of geriatrics and gerontology because it is related to the risk of falling and subsequent morbidity of falling. This study seeks to classify the acceleration patterns of the center of mass during walking in subjects with mild and moderate knee osteoarthritis (KOA) for three levels of FOF (mild, moderate, and high). (2) Method: Center-of-mass acceleration patterns were recorded in all three planes of motion for a 30-meter walk test. A convolutional neural network (CNN) was implemented for the classification of acceleration signals based on the different levels of FOF (mild, moderate, and high) for two KOA conditions (mild and moderate). (3) Results: For the three levels of FOF to fall and regardless of the degree of KOA, a precision of 0.71 was obtained. For the classification considering the three levels of FOF and only for the mild KOA condition, a precision of 0.72 was obtained. For the classification considering the three levels of FOF and only the moderate KOA condition, a precision of 0.81 was obtained, the same as in the previous case, and finally for the classification for two levels of FOF, a high vs. moderate precision of 0.78 was obtained. For high vs. low, a precision of 0.77 was obtained, and for the moderate vs. low, a precision of 0.8 was obtained. Finally, when considering both KOA conditions, a 0.74 rating was obtained. (4) Conclusions: The classification model based on deep learning (CNN) allows for the adequate discrimination of the acceleration patterns of the moderate class above the low or high FOF. © 2022 by the authors.es
dc.description.urihttps://www.mdpi.com/1660-4601/19/19/12890
dc.identifier.citationInternational Journal of Environmental Research and Public Health, Volume 19, Issue 19, October 2022, Article number 12890es
dc.identifier.doi10.3390/ijerph191912890
dc.identifier.issn1661-7827
dc.identifier.urihttps://repositorio.unab.cl/xmlui/handle/ria/52437
dc.language.isoenes
dc.publisherMDPIes
dc.rights.licenseAtribución 4.0 Internacional (CC BY 4.0)
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/deed.es
dc.subjectAccelerationes
dc.subjectDeep learninges
dc.subjectFalles
dc.subjectGaites
dc.subjectKnee osteoarthritises
dc.subjectPreoccupationes
dc.titleClassification of Center of Mass Acceleration Patterns in Older People with Knee Osteoarthritis and Fear of Fallinges
dc.typeArtículoes
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