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dc.contributor.authorCarneros-Prado, David
dc.contributor.authorDobrescu, Cosmin C.
dc.contributor.authorGonzález, Iván
dc.contributor.authorFontecha, Jesús
dc.contributor.authorJohnson Ruiz, Maria Esperanza
dc.contributor.authorHervás, Ramón
dc.date.accessioned2024-04-03T09:09:06Z
dc.date.available2024-04-03T09:09:06Z
dc.date.created2023-12-14T10:40:43Z
dc.date.issued2023
dc.identifier.issn2227-7390
dc.identifier.urihttps://hdl.handle.net/11250/3124618
dc.descriptionThis 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/).en_US
dc.description.abstractCognitive deficits are very difficult to diagnose during the initial stages; tests typically consist of a patient performing punctual dual-task activities, which are subjectively analyzed to determine the cognitive decline impact on gait. This work supports novel and objective diagnosis methods by stating a baseline on how neurotypical aging affects dual tasks while using a smartphone on the move. With this aim, we propose a twofold research question: Which mobile device tasks performed on the move (dual tasking) have characteristic changes in gait parameters, and which are especially characteristic at older ages? An experiment was conducted with 30 healthy participants where they performed 15 activities (1 single task, 2 traditional dual-tasks and 12 mobile-based dual-tasks) while walking about 50 m. Participants wore a wireless motion tracker (15 sensors) that made the concise analysis of gait possible. The results obtained characterized the gait parameters affected by mobile-based dual-tasking and the impact of normal cognitive decline due to aging. The statistical analysis shows that using smartphone-based dual-tasking produces more significant results than traditional dual-tasking. In the study, 3 out of 10 gait parameters were very significantly affected (p < 0.001) when using the traditional dual tasks, while 5 out of 10 parameters were very significantly affected (p < 0.001) in mobile-based dual-tasking. Moreover, the most characteristic tasks and gait parameters were identified through the obtained results. Future work will focus on applying this knowledge to improve the early diagnosis of MCI.en_US
dc.language.isoengen_US
dc.publisherMDPIen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleAnalysis of Dual-Tasking Effect on Gait Variability While Interacting with Mobile Devicesen_US
dc.title.alternativeAnalysis of Dual-Tasking Effect on Gait Variability While Interacting with Mobile Devicesen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.rights.holder© 2022 by the authors. Licensee MDPI, Basel, Switzerlanden_US
dc.source.volume11en_US
dc.source.journalMathematicsen_US
dc.source.issue1en_US
dc.identifier.doi10.3390/math11010202
dc.identifier.cristin2213485
dc.source.articlenumber202en_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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Navngivelse 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Navngivelse 4.0 Internasjonal