RT Journal Article
T1 A framework for user adaptation and profiling for social robotics in rehabilitation
A1 Martín, Alejandro
A1 Pulido Pascual, José Carlos
A1 González Dorado, José Carlos
A1 García Olaya, Ángel
A1 Suárez  Mejías, Cristina
AB Physical 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 metric
PB MDPI
SN 1424-8220
YR 2020
FD 2020-08-25
LK https://hdl.handle.net/10016/34500
UL https://hdl.handle.net/10016/34500
LA eng
NO This work is partially funded by grant RTI2018-099522-B-C43 of FEDER/Ministerio de Ciencia e Innovación - Ministerio de Universidades - Agencia Estatal de Investigación
DS e-Archivo
RD 17 jul. 2024