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A framework for user adaptation and profiling for social robotics in rehabilitation

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dc.affiliation.dptoUC3M. Departamento de Informáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Planificación y Aprendizajees
dc.contributor.authorMartín, Alejandro
dc.contributor.authorPulido Pascual, José Carlos
dc.contributor.authorGonzález Dorado, José Carlos
dc.contributor.authorGarcía Olaya, Ángel
dc.contributor.authorSuárez Mejías, Cristina
dc.contributor.funderAgencia Estatal de Investigación (España)es
dc.date.accessioned2022-03-31T08:25:22Z
dc.date.available2022-03-31T08:25:22Z
dc.date.issued2020-08-25
dc.description.abstractPhysical rehabilitation therapies for children present a challenge, and its success—the improvement of the patient’s condition—depends on many factors, such as the patient’s attitude and motivation, the correct execution of the exercises prescribed by the specialist or his progressive recovery during the therapy. With the aim to increase the benefits of these therapies, social humanoid robots with a friendly aspect represent a promising tool not only to boost the interaction with the pediatric patient, but also to assist physicians in their work. To achieve both goals, it is essential to monitor in detail the patient’s condition, trying to generate user profile models which enhance the feedback with both the system and the specialist. This paper describes how the project NAOTherapist—a robotic architecture for rehabilitation with social robots—has been upgraded in order to include a monitoring system able to generate user profile models through the interaction with the patient, performing user-adapted therapies. Furthermore, the system has been improved by integrating a machine learning algorithm which recognizes the pose adopted by the patient and by adding a clinical reports generation system based on the QUEST metricen
dc.description.sponsorshipThis work is partially funded by grant RTI2018-099522-B-C43 of FEDER/Ministerio de Ciencia e Innovación - Ministerio de Universidades - Agencia Estatal de Investigaciónen
dc.identifier.bibliographicCitationMartín, A.; Pulido, J.C.; González, J.C.; García-Olaya, Á.; Suárez, C. A Framework for User Adaptation and Profiling for Social Robotics in Rehabilitation. Sensors 2020, 20, 4792. https://doi.org/10.3390/s20174792en
dc.identifier.doihttps://doi.org/10.3390/s20174792
dc.identifier.issn1424-8220
dc.identifier.publicationfirstpage1
dc.identifier.publicationissue17
dc.identifier.publicationlastpage23
dc.identifier.publicationtitleSENSORSen
dc.identifier.publicationvolume20
dc.identifier.urihttps://hdl.handle.net/10016/34500
dc.identifier.uxxiAR/0000026192
dc.language.isoengen
dc.publisherMDPIen
dc.relation.projectIDGobierno de España. RTI2018-099522-B-C43es
dc.rights© 2020 by the authors. Licensee MDPIen
dc.rightsAtribución 3.0 España
dc.rights.accessRightsopen accessen
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/
dc.subject.ecienciaInformáticaes
dc.subject.otheruser profilingen
dc.subject.otherrehabilitationen
dc.subject.othersocial roboten
dc.subject.othermachine learningen
dc.titleA framework for user adaptation and profiling for social robotics in rehabilitationen
dc.typeresearch article*
dc.type.hasVersionVoR*
dspace.entity.typePublication
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