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dc.contributor.author | Navarro-Alamán, Javier | es_ES |
dc.contributor.author | Lacuesta Gilaberte, Raquel | es_ES |
dc.contributor.author | García-Magariño, Iván | es_ES |
dc.contributor.author | Gallardo, Jesús | es_ES |
dc.contributor.author | Ibarz, Elena | es_ES |
dc.contributor.author | Lloret, Jaime | es_ES |
dc.date.accessioned | 2022-11-07T16:33:47Z | |
dc.date.available | 2022-11-07T16:33:47Z | |
dc.date.issued | 2020-07-15 | es_ES |
dc.identifier.issn | 2040-2295 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/189320 | |
dc.description.abstract | [EN] The management of cancer patients' symptoms in doctor consultations is a cornerstone in clinical care, this process being fundamental for the follow-up of the evolution of these. This article presents an application that allows collecting periodically and systematically the data of cancer patients and their visualization by the medical team. In this article, we made the analysis, design, implementation, and final evaluation by analyzing the correlation of this data collection with interaction patterns to determine how the user information can be enriched with information from the interaction patterns. We have followed an agile methodology based on the iterative and incremental development of successive prototypes with increased fidelity, where the requirements and solutions have evolved over time according to the need and assessments made. The comprehensive analysis of the patient's condition allowed us to perform a first analysis of the correlation of the states of patients concerning mood, sleeping quality, and pain with the interaction patterns. A future goal of this project is to optimize the process of data collection and the analysis of information. Another future goal is to reduce the time dedicated to reporting the evolution of symptoms in face-to-face consultations and to help professionals in analyzing the patient's evolution even in the period that has not been attended in person. | es_ES |
dc.description.sponsorship | The authors would like to thank the psychologists of the AECC of Teruel for their willingness to help them in improving the application. This work was funded by the research projects "New Technologies in Cancer Monitoring and Treatment" and "Advances in Research, Diagnosis and Monitoring of Bone Cancer Patients as a Primary or Secondary Tumor" by the University Foundation "Antonio Gargallo." This work was partly funded by the Spanish Science, Innovation and University Ministry (MCIU), the National Research Agency (AEI), and the EU (FEDER) through the contract RTI2018-096986-B-C31 and by the Aragonese Government and the EU through the FEDER 2014-2020 "Construyendo Europa desde Aragon" action (Group T25_17D). They also acknowledge the partial support from CYTED (ref. 518RT0558) and MCIU (TIN201788327-R). | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Hindawi Limited | es_ES |
dc.relation.ispartof | Journal of Healthcare Engineering | es_ES |
dc.rights | Reconocimiento (by) | es_ES |
dc.title | Close2U: An App for Monitoring Cancer Patients with Enriched Information from Interaction Patterns | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1155/2020/3057032 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2017-88327-R/ES/DISEÑO COLABORATIVO PARA LA PROMOCION DEL BIENESTAR EN CIUDADES INTELIGENTES INCLUSIVAS/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/CYTED//518RT0558/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-096986-B-C31/ES/EXPERIENCIAS DE JUEGO PERVASIVAS PARA TODOS/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/Gobierno de Aragón//T25_17D/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.description.bibliographicCitation | Navarro-Alamán, J.; Lacuesta Gilaberte, R.; García-Magariño, I.; Gallardo, J.; Ibarz, E.; Lloret, J. (2020). Close2U: An App for Monitoring Cancer Patients with Enriched Information from Interaction Patterns. Journal of Healthcare Engineering. 2020:1-13. https://doi.org/10.1155/2020/3057032 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.1155/2020/3057032 | es_ES |
dc.description.upvformatpinicio | 1 | es_ES |
dc.description.upvformatpfin | 13 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 2020 | es_ES |
dc.identifier.pmid | 32733661 | es_ES |
dc.identifier.pmcid | PMC7378616 | es_ES |
dc.relation.pasarela | S\473171 | es_ES |
dc.contributor.funder | Gobierno de Aragón | es_ES |
dc.contributor.funder | Agencia Estatal de Investigación | es_ES |
dc.contributor.funder | CYTED Ciencia y Tecnología para el Desarrollo | es_ES |