Robotic-Based Well-Being Monitoring and Coaching System for the Elderly in Their Daily Activities
Francisco M. Calatrava-Nicolás,
Eduardo Gutiérrez-Maestro,
Daniel Bautista-Salinas,
Francisco J. Ortiz,
Joaquín Roca González,
José Alfonso Vera-Repullo,
Manuel Jiménez-Buendía,
Inmaculada Méndez,
Cecilia Ruiz-Esteban,
Oscar Martínez Mozos
Affiliations
Francisco M. Calatrava-Nicolás
ETSII (Escuela Técnica Superior de Ingeniería Industrial), Technical University of Cartagena, St. Dr. Fleming, s/n, 30203 Cartagena, Spain
Eduardo Gutiérrez-Maestro
AASS (Applied Autonomous Sensor Systems), Örebro University, 70281 Örebro, Sweden
Daniel Bautista-Salinas
The Hamlyn Centre for Robotic Surgery, Imperial College London, London SW7 2AZ, UK
Francisco J. Ortiz
ETSII (Escuela Técnica Superior de Ingeniería Industrial), Technical University of Cartagena, St. Dr. Fleming, s/n, 30203 Cartagena, Spain
Joaquín Roca González
ETSII (Escuela Técnica Superior de Ingeniería Industrial), Technical University of Cartagena, St. Dr. Fleming, s/n, 30203 Cartagena, Spain
José Alfonso Vera-Repullo
ETSII (Escuela Técnica Superior de Ingeniería Industrial), Technical University of Cartagena, St. Dr. Fleming, s/n, 30203 Cartagena, Spain
Manuel Jiménez-Buendía
ETSII (Escuela Técnica Superior de Ingeniería Industrial), Technical University of Cartagena, St. Dr. Fleming, s/n, 30203 Cartagena, Spain
Inmaculada Méndez
Department of Evolutionary and Educational Psychology, Faculty of Psychology, Campus Regional Excellence Mare Nostrum, University of Murcia, 30100 Murcia, Spain
Cecilia Ruiz-Esteban
Department of Evolutionary and Educational Psychology, Faculty of Psychology, Campus Regional Excellence Mare Nostrum, University of Murcia, 30100 Murcia, Spain
Oscar Martínez Mozos
AASS (Applied Autonomous Sensor Systems), Örebro University, 70281 Örebro, Sweden
The increasingly ageing population and the tendency to live alone have led science and engineering researchers to search for health care solutions. In the COVID 19 pandemic, the elderly have been seriously affected in addition to suffering from isolation and its associated and psychological consequences. This paper provides an overview of the RobWell (Robotic-based Well-Being Monitoring and Coaching System for the Elderly in their Daily Activities) system. It is a system focused on the field of artificial intelligence for mood prediction and coaching. This paper presents a general overview of the initially proposed system as well as the preliminary results related to the home automation subsystem, autonomous robot navigation and mood estimation through machine learning prior to the final system integration, which will be discussed in future works. The main goal is to improve their mental well-being during their daily household activities. The system is composed of ambient intelligence with intelligent sensors, actuators and a robotic platform that interacts with the user. A test smart home system was set up in which the sensors, actuators and robotic platform were integrated and tested. For artificial intelligence applied to mood prediction, we used machine learning to classify several physiological signals into different moods. In robotics, it was concluded that the ROS autonomous navigation stack and its autodocking algorithm were not reliable enough for this task, while the robot’s autonomy was sufficient. Semantic navigation, artificial intelligence and computer vision alternatives are being sought.
