125256 20241125101136.0 doi 10.3390/s23031608 sideral 132986 ART-2023-132986 eng Baldassarri, Sandra Universidad de Zaragoza (orcid)0000-0002-9315-6391 Wearables and machine learning for improving runners’ motivation from an affective perspective 2023 Access copy available to the general public Unrestricted Wearable technology is playing an increasing role in the development of user-centric applications. In the field of sports, this technology is being used to implement solutions that improve athletes’ performance, reduce the risk of injury, or control fatigue, for example. Emotions are involved in most of these solutions, but unfortunately, they are not monitored in real-time or used as a decision element that helps to increase the quality of training sessions, nor are they used to guarantee the health of athletes. In this paper, we present a wearable and a set of machine learning models that are able to deduce runners’ emotions during their training. The solution is based on the analysis of runners’ electrodermal activity, a physiological parameter widely used in the field of emotion recognition. As part of the DJ-Running project, we have used these emotions to increase runners’ motivation through music. It has required integrating the wearable and the models into the DJ-Running mobile application, which interacts with the technological infrastructure of the project to select and play the most suitable songs at each instant of the training. info:eu-repo/grantAgreement/ES/MINECO/PDC2021-121072-C22 info:eu-repo/grantAgreement/ES/RTI2018-096986-B-C31 info:eu-repo/grantAgreement/EUR/MINECO/TED2021-130374B-C22 info:eu-repo/semantics/openAccess by http://creativecommons.org/licenses/by/3.0/es/ 3.4 2023 CHEMISTRY, ANALYTICAL 34 / 106 = 0.321 2023 Q2 T1 INSTRUMENTS & INSTRUMENTATION 24 / 76 = 0.316 2023 Q2 T1 ENGINEERING, ELECTRICAL & ELECTRONIC 122 / 353 = 0.346 2023 Q2 T2 0.786 2023 Instrumentation 2023 Q1 Analytical Chemistry 2023 Q1 Atomic and Molecular Physics, and Optics 2023 Q1 Information Systems 2023 Q2 Medicine (miscellaneous) 2023 Q2 Biochemistry 2023 Q2 Electrical and Electronic Engineering 2023 Q2 7.3 2023 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion García de Quirós, Jorge Universidad de Zaragoza Beltrán, José Ramón Universidad de Zaragoza (orcid)0000-0002-7500-4650 Álvarez, Pedro Universidad de Zaragoza (orcid)0000-0002-6584-7259 5008 785 Universidad de Zaragoza Dpto. Ingeniería Electrón.Com. Área Tecnología Electrónica 5007 570 Universidad de Zaragoza Dpto. Informát.Ingenie.Sistms. Área Lenguajes y Sistemas Inf. 23, 3 (2023), 1608 [16 pp] Sensors Sensors 1424-8220 3529895 http://zaguan.unizar.es/record/125256/files/texto_completo.pdf Versión publicada 2695000 http://zaguan.unizar.es/record/125256/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:125256 articulos driver 2024-11-22-12:00:50 ARTICLE