Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/85463

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Campo DCValorIdioma
dc.contributor.authorCunha, Pedropor
dc.contributor.authorBarbosa, Paulopor
dc.contributor.authorFerreira, Fábiopor
dc.contributor.authorSilva, Tâniapor
dc.contributor.authorMartins, Nunopor
dc.contributor.authorSoares, Filomenapor
dc.contributor.authorCarvalho, Vítorpor
dc.date.accessioned2023-07-10T13:55:30Z-
dc.date.available2023-07-10T13:55:30Z-
dc.date.issued2023-02-05-
dc.identifier.citationCunha, P.; Barbosa, P.; Ferreira, F.; Silva, T.; Martins, N.; Soares, F.; Carvalho, V. Cyber-Physical System for Evaluation of Taekwondo Athletes: An Initial Project Description. Machines 2023, 11, 234. https://doi.org/10.3390/machines11020234por
dc.identifier.urihttps://hdl.handle.net/1822/85463-
dc.description.abstractRegardless of the type of sport, coaches must perform the difficult task of evaluating the performance of athletes. In some cases, this task is aided using technology which provides tools for this purpose. When the sport considered is taekwondo this scenario does not apply as the athlete evaluation methods used are mostly manual. Thus, the project presented in this paper has the main objective to develop a system that can be used as a tool to evaluate the performance of taekwondo athletes in real time, with special attention to the low cost of implementation and ease of use. With the intention of meeting these requirements, the developed system comprises a 3D camera with a depth sensor (Orbbec Astra), Inertial Measurement Units (IMUs) with accelerometer and gyroscope, a computer and specific software developed for this purpose. This system allows the collection of data from the athletes’ movements necessary for the creation of a dataset that is then analyzed and interpretated. The system permits the user to obtain real-time information about the speed, acceleration, and strength of the athlete’s limbs during training as well as the identification of some movements and their accounting. To achieve this functionality, deep-learning architecture models were used, more specifically long short-term memory (LSTM). The intention is to provide a new training methodology through faster feedback, so that a faster evolution of the athlete’s performance is possible, contributing to the technological development of the assessment practices used in taekwondo.por
dc.description.sponsorshipThis research was funded by FCT—Fundação para a Ciência e Tecnologia (Portugal) grant number SFRH/BD/121994/2016 and FCT RD Units Projects Scope: UIDB/04077/2020, UIDB/00319/2020, UIDB/05549/2020 and UIDP/05549/2020.por
dc.language.isoengpor
dc.publisherMultidisciplinary Digital Publishing Institutepor
dc.relationinfo:eu-repo/grantAgreement/FCT/POR_NORTE/SFRH%2FBD%2F121994%2F2016/PTpor
dc.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04077%2F2020/PTpor
dc.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00319%2F2020/PTpor
dc.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F05549%2F2020/PTpor
dc.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F05549%2F2020/PTpor
dc.rightsopenAccesspor
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/por
dc.subjectDeep-learningpor
dc.subjectMotion analysispor
dc.subjectNeural networkspor
dc.subjectWearablespor
dc.subjectComputer visionpor
dc.subjectTaekwondopor
dc.titleCyber-physical system for evaluation of Taekwondo athletes: an initial project descriptionpor
dc.typearticlepor
dc.peerreviewedyespor
dc.relation.publisherversionhttps://www.mdpi.com/2075-1702/11/2/234por
oaire.citationStartPage1por
oaire.citationEndPage22por
oaire.citationIssue2por
oaire.citationVolume11por
dc.date.updated2023-02-24T14:09:25Z-
dc.identifier.eissn2075-1702-
dc.identifier.doi10.3390/machines11020234por
dc.subject.wosScience & Technologypor
sdum.journalMachinespor
oaire.versionVoRpor
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