000087632 001__ 87632 000087632 005__ 20200716101551.0 000087632 0247_ $$2doi$$a10.3390/s19225004 000087632 0248_ $$2sideral$$a115862 000087632 037__ $$aART-2019-115862 000087632 041__ $$aeng 000087632 100__ $$aBenages Pardo, Luis$$uUniversidad de Zaragoza 000087632 245__ $$aDetection of tennis activities with wearable sensors 000087632 260__ $$c2019 000087632 5060_ $$aAccess copy available to the general public$$fUnrestricted 000087632 5203_ $$aThis paper aims to design and implement a system capable of distinguishing between different activities carried out during a tennis match. The goal is to achieve the correct classification of a set of tennis strokes. The system must exhibit robustness to the variability of the height, age or sex of any subject that performs the actions. A new database is developed to meet this objective. The system is based on two sensor nodes using Bluetooth Low Energy (BLE) wireless technology to communicate with a PC that acts as a central device to collect the information received by the sensors. The data provided by these sensors are processed to calculate their spectrograms. Through the application of innovative deep learning techniques with semi-supervised training, it is possible to carry out the extraction of characteristics and the classification of activities. Preliminary results obtained with a data set of eight players, four women and four men have shown that our approach is able to address the problem of the diversity of human constitutions, weight and sex of different players, providing accuracy greater than 96.5% to recognize the tennis strokes of a new player never seen before by the system. 000087632 536__ $$9info:eu-repo/grantAgreement/ES/MINECO/TIN2017-88841-R 000087632 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/ 000087632 590__ $$a3.275$$b2019 000087632 591__ $$aCHEMISTRY, ANALYTICAL$$b22 / 86 = 0.256$$c2019$$dQ2$$eT1 000087632 591__ $$aINSTRUMENTS & INSTRUMENTATION$$b15 / 64 = 0.234$$c2019$$dQ1$$eT1 000087632 591__ $$aENGINEERING, ELECTRICAL & ELECTRONIC$$b77 / 266 = 0.289$$c2019$$dQ2$$eT1 000087632 592__ $$a0.653$$b2019 000087632 593__ $$aInstrumentation$$c2019$$dQ1 000087632 593__ $$aAtomic and Molecular Physics, and Optics$$c2019$$dQ2 000087632 593__ $$aMedicine (miscellaneous)$$c2019$$dQ2 000087632 593__ $$aInformation Systems$$c2019$$dQ2 000087632 593__ $$aAnalytical Chemistry$$c2019$$dQ2 000087632 593__ $$aElectrical and Electronic Engineering$$c2019$$dQ2 000087632 593__ $$aBiochemistry$$c2019$$dQ3 000087632 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion 000087632 700__ $$0(orcid)0000-0003-3431-5863$$aBuldain Perez, David$$uUniversidad de Zaragoza 000087632 700__ $$0(orcid)0000-0002-0903-5520$$aOrrite Uruñuela, Carlos$$uUniversidad de Zaragoza 000087632 7102_ $$15007$$2520$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Ingen.Sistemas y Automát. 000087632 7102_ $$15008$$2785$$aUniversidad de Zaragoza$$bDpto. Ingeniería Electrón.Com.$$cÁrea Tecnología Electrónica 000087632 773__ $$g19, 22 (2019), 5004 [19 pp.]$$pSensors$$tSensors (Switzerland)$$x1424-8220 000087632 8564_ $$s1300602$$uhttps://zaguan.unizar.es/record/87632/files/texto_completo.pdf$$yVersión publicada 000087632 8564_ $$s111072$$uhttps://zaguan.unizar.es/record/87632/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada 000087632 909CO $$ooai:zaguan.unizar.es:87632$$particulos$$pdriver 000087632 951__ $$a2020-07-16-09:46:01 000087632 980__ $$aARTICLE