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Robotic-Based Well-Being Monitoring and Coaching System for the Elderly in Their Daily Activities

Authors :
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
Source :
Sensors, Vol 21, Iss 20, p 6865 (2021)
Publication Year :
2021
Publisher :
MDPI AG, 2021.

Abstract

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.

Details

Language :
English
ISSN :
14248220
Volume :
21
Issue :
20
Database :
Directory of Open Access Journals
Journal :
Sensors
Publication Type :
Academic Journal
Accession number :
edsdoj.7fc37fbfc3a54ff697979429c3ab799d
Document Type :
article
Full Text :
https://doi.org/10.3390/s21206865