Publication: Relevance of sex, age and gait kinematics when predicting fall-risk and mortality in older adults
| dc.contributor.author | Porta Cuéllar, Sonia | |
| dc.contributor.author | Martínez Ramírez, Alicia | |
| dc.contributor.author | Millor Muruzábal, Nora | |
| dc.contributor.author | Gómez Fernández, Marisol | |
| dc.contributor.author | Izquierdo Redín, Mikel | |
| dc.contributor.department | Ingeniería Eléctrica, Electrónica y de Comunicación | es_ES |
| dc.contributor.department | Estadística, Informática y Matemáticas | es_ES |
| dc.contributor.department | Ciencias de la Salud | es_ES |
| dc.contributor.department | Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren | eu |
| dc.contributor.department | Estatistika, Informatika eta Matematika | eu |
| dc.contributor.department | Osasun Zientziak | eu |
| dc.contributor.funder | Gobierno de Navarra / Nafarroako Gobernua, 87/10 | es |
| dc.date.accessioned | 2021-02-19T08:12:02Z | |
| dc.date.available | 2022-05-22T23:00:15Z | |
| dc.date.issued | 2020 | |
| dc.description.abstract | Approximately one-third of elderly people fall each year with severe consequences, including death. The aim of this study was to identify the most relevant features to be considered to maximize the accuracy of a logistic regression model designed for prediction of fall/mortality risk among older people. This study included 261 adults, aged over 65 years. Men and women were analyzed separately because sex stratification was revealed as being essential for our purposes of feature ranking and selection. Participants completed a 3-m walk test at their own gait velocity. An inertial sensor attached to their lumbar spine was used to record acceleration data in the three spatial directions. Signal processing techniques allowed the extraction of 21 features representative of gait kinematics, to be used as predictors to train and test the model. Age and gait speed data were also considered as predictors. A set of 23 features was considered. These features demonstrate to be more or less relevant depending on the sex of the cohort under analysis and the classification label (risk of falls and mortality). In each case, the minimum size subset of relevant features is provided to show the maximum accuracy prediction capability. Gait speed has been largely used as the single feature for the prediction fall risk among older adults. Nevertheless, prediction accuracy can be substantially improved, reaching 70% in some cases, if the task of training and testing the model takes into account some other features, namely, sex, age and gait kinematic parameters. Therefore we recommend considering sex, age and step regularity to predict fall-risk. | en |
| dc.description.sponsorship | This work was supported by the Spanish Ministry of Health, Institute Carlos III [grant numbers RD06/013/1003, RD12/0043/0002] and by the Department of Health of the Government of Navarra [grant number 87/10] as well as by a research grant PI17/01814 of the Ministerio de Economía, Industria y Competitividad (ISCIII, FEDER). | en |
| dc.embargo.lift | 2022-05-22 | |
| dc.embargo.terms | 2022-05-22 | |
| dc.format.extent | 18 p. | |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.doi | 10.1016/j.jbiomech.2020.109723 | |
| dc.identifier.issn | 0021-9290 | |
| dc.identifier.uri | https://academica-e.unavarra.es/handle/2454/39250 | |
| dc.language.iso | eng | en |
| dc.publisher | Elsevier | en |
| dc.relation.ispartof | Journal of Biomechanics, 2020, 105, 109723 | en |
| dc.relation.publisherversion | https://doi.org/10.1016/j.jbiomech.2020.109723 | |
| dc.rights | © 2020 Elsevier Ltd. This manuscript version is made available under the CC-BY-NC-ND 4.0 | en |
| dc.rights.accessRights | info:eu-repo/semantics/openAccess | en |
| dc.rights.accessRights | Acceso abierto / Sarbide irekia | es |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.subject | Prediction of falls/mortality risk | en |
| dc.subject | Logistic regression model | en |
| dc.subject | Feature selection for maximum accuracy prediction | en |
| dc.subject | Sex stratification importance | en |
| dc.title | Relevance of sex, age and gait kinematics when predicting fall-risk and mortality in older adults | en |
| dc.type | info:eu-repo/semantics/article | en |
| dc.type | Artículo / Artikulua | es |
| dc.type.version | info:eu-repo/semantics/acceptedVersion | en |
| dc.type.version | Versión aceptada / Onetsi den bertsioa | es |
| dspace.entity.type | Publication | |
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