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dc.contributor.authorAriza Colpas, Paola Patriciaspa
dc.contributor.authorOñate-Bowen, Alvaro Agustínspa
dc.contributor.authorSuarez-Brieva, Eydy del Carmenspa
dc.contributor.authorOviedo Carrascal, Ana Isabelspa
dc.contributor.authorUrina Triana, Miguelspa
dc.contributor.authorPiñeres Melo, Marlon Albertospa
dc.contributor.authorButt Shariq, Azizspa
dc.contributor.authorCOLLAZOS MORALES, CARLOS ANDRESspa
dc.contributor.authorRamayo González, Ramón Enriquespa
dc.date.accessioned2021-09-15T15:03:24Z
dc.date.available2021-09-15T15:03:24Z
dc.date.issued2021
dc.identifier.issn1877-0509spa
dc.identifier.urihttps://hdl.handle.net/11323/8696spa
dc.description.abstractReminders are a core component of many assistive technology systems and are aimed specifically at helping people with dementia function more independently by compensating for cognitive deficits. These technologies are often utilized for prospective reminding, reminiscence, or within coaching-based systems. Traditionally, reminders have taken the form of nontechnology based aids, such as diaries, notebooks, cue cards and white boards. This article is based on the use of machine learning algorithms for the detection of Alzheimer’s disease. In the experimentation, the LWL, SimpleLogistic, Logistic, MultiLayerPercepton and HiperPipes algorithms were used. The result showed that the LWL algorithm produced the following results: Accuracy 98.81%, Precission 100%, Recall 97.62% and F- measure 98.80%spa
dc.format.mimetypeapplication/pdfspa
dc.language.isoeng
dc.publisherCorporación Universidad de la Costaspa
dc.rightsCC0 1.0 Universalspa
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/spa
dc.sourceProcedia Computer Sciencespa
dc.subjectMachine learningspa
dc.subjectHARADLspa
dc.subjectHuman activity recognitionspa
dc.subjectActivity daily livingspa
dc.subjectVanKasteren datasetspa
dc.titleMachine learning approach applied to human activity recognition – an application to the VanKasteren datasetspa
dc.typeArtículo de revistaspa
dc.source.urlhttps://www.sciencedirect.com/science/article/pii/S1877050921014733spa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.identifier.doihttps://doi.org/10.1016/j.procs.2021.07.070spa
dc.identifier.instnameCorporación Universidad de la Costaspa
dc.identifier.reponameREDICUC - Repositorio CUCspa
dc.identifier.repourlhttps://repositorio.cuc.edu.co/spa
dc.relation.references[1] Sohn, T., Li, K. A., Lee, G., Smith, I., Scott, J., & Griswold, W. G. (2005, September). Place-its: A study of location-based reminders on mobile phones. In International Conference on Ubiquitous Computing (pp. 232-250). Springer, Berlin, Heidelberg.spa
dc.relation.references[2] Sumi Helal, Carlos Giraldo, Youssef Kaddoura, Choonhwa Lee, Hicham El Zabadani, and William Mann. Smart phone based cognitive assistant. In UbiHealth 2003: The 2nd International Workshop on Ubiquitous Computing for Pervasive Healthcare Applications, 2003.spa
dc.relation.references[3] Pollock, P. M., Harper, U. L., Hansen, K. S., Yudt, L. M., Stark, M., Robbins, C. M., ... & Salem, G. (2003). High frequency of BRAF mutations in nevi. Nature genetics, 33(1), 19-20.spa
dc.relation.references[4] Oliver Zangwill Centre Neuropsychological Rehabilitation Accessed December 2014. NeuroPage. Online, http://www.neuropage.nhs.uk/, 2014.spa
dc.relation.references[5] Barbara A Wilson, Jonathan J Evans, Hazel Emslie, and Vlastimil Malinek. Evaluation of neuropage: a new memory aid. Journal of Neurology, Neurosurgery & Psychiatry, 63(1):113–115, 1997.spa
dc.relation.references[6] Barbara A Wilson, Helena Scott, Jonathan Evans, and Hazel Emslie. Preliminary report of a neuropage service within a health care system. NeuroRehabilitation, 18(1):3–8, 2003.spa
dc.relation.references[7] Wilson, HC Emslie, K Quirk, and JJ Evans. Reducing everyday memory and planning problems by means of a paging system: a randomised control crossover study. Journal of Neurology, Neurosurgery & Psychiatry, 70(4):477–482, 2001spa
dc.relation.references[8] Zhou, J., Gennatas, E. D., Kramer, J. H., Miller, B. L., & Seeley, W. W. (2012). Predicting regional neurodegeneration from the healthy brain functional connectome. Neuron, 73(6), 1216-1227.spa
dc.relation.references[9] ati nneli annisto, arita annele oivunen, and aritta nneli lim ki. se of mobile phone text message reminders in health care services: A narrative literature review. Journal of medical Internet research, 16(10), 2014.spa
dc.type.coarhttp://purl.org/coar/resource_type/c_6501spa
dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/articlespa
dc.type.redcolhttp://purl.org/redcol/resource_type/ARTspa
dc.type.versioninfo:eu-repo/semantics/acceptedVersionspa
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
dc.rights.coarhttp://purl.org/coar/access_right/c_abf2spa


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