dc.contributor.author | Fister, Iztok Jr. | |
dc.contributor.author | Salcedo-Sanz, Sancho | |
dc.contributor.author | Iglesias Prieto, Andrés | |
dc.contributor.author | Fister, Dušan | |
dc.contributor.author | Gálvez Tomida, Akemi | |
dc.contributor.author | Fister, Iztok | |
dc.contributor.other | Universidad de Cantabria | es_ES |
dc.date.accessioned | 2022-01-14T14:40:53Z | |
dc.date.available | 2022-01-14T14:40:53Z | |
dc.date.issued | 2021 | |
dc.identifier.issn | 2076-3417 | |
dc.identifier.other | TIN2017-89275-R | es_ES |
dc.identifier.other | MCIN/AEI /10.13039/501100011033/FEDER | es_ES |
dc.identifier.uri | http://hdl.handle.net/10902/23735 | |
dc.description.abstract | The rapid development of computer science and telecommunications has brought new ways and practices to sport training. The artificial sport trainer, founded on computational intelligence algorithms, has gained momentum in the last years. However, artificial sport trainer usually suffers from a lack of automatisation in realization and control phases of the training. In this study, the Digital Twin is proposed as a framework for helping athletes, during realization of training sessions, to make the proper decisions in situations they encounter. The digital twin for artificial sport trainer is based on the cognitive model of humans. This concept has been applied to cycling, where a version of the system on a Raspberry Pi already exists. The results of porting the digital twin on the mentioned platform shows promising potential for its extension to other sport disciplines. | es_ES |
dc.description.sponsorship | Akemi Galvez and Andres Iglesias have received funding from the project PDE-GIR of the
European Union’s Horizon 2020 research and innovation programme under the Marie SklodowskaCurie grant agreement no. 778035, and from the project TIN2017-89275-R funded by MCIN/AEI/10.13039/501100011033/FEDER “Una manera de hacer Europa”. | es_ES |
dc.format.extent | 14 p. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | MDPI | es_ES |
dc.rights | Attribution 4.0 International. © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
dc.source | Applied Sciences, 2021, 11(23), 11452 | es_ES |
dc.subject.other | Artificial sport trainer | es_ES |
dc.subject.other | Digital twin | es_ES |
dc.subject.other | Cognitive models | es_ES |
dc.subject.other | Computational intelligence | es_ES |
dc.title | New perspectives in the development of the artificial sport trainer | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.relation.publisherVersion | https://doi.org/10.3390/app112311452 | es_ES |
dc.rights.accessRights | openAccess | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/H2020/778035/EU/PDE-based geometric modelling, image processing, and shape reconstruction/PDE-GIR/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2017-89275-R/ES/SWARM INTELLIGENCE PARA MODELADO Y RECONSTRUCCION DE FORMAS EN GRAFICOS POR COMPUTADOR, IMAGENES MEDICAS Y ROBOTICA/ | es_ES |
dc.identifier.DOI | 10.3390/app112311452 | |
dc.type.version | publishedVersion | es_ES |