Robotic-Based Well-Being Monitoring and Coaching System for the Elderly in Their Daily Activities
| Autor: | Manuel Jiménez-Buendía, Joaquín Roca González, Eduardo Gutiérrez-Maestro, Inmaculada Méndez, Francisco J. Ortiz, Francisco M. Calatrava-Nicolás, Cecilia Ruiz-Esteban, José Alfonso Vera-Repullo, Daniel Bautista-Salinas, Oscar Martinez Mozos |
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| Rok vydání: | 2021 |
| Předmět: |
Activities of daily living
smart home Computer science TP1-1185 Biochemistry Coaching Article Analytical Chemistry Artificial Intelligence Home automation Human–computer interaction Humans Electrical and Electronic Engineering affective computing Affective computing Instrumentation Aged assistive robotics Ambient intelligence ambient assisted living SARS-CoV-2 business.industry Chemical technology mood prediction COVID-19 Mentoring ROS Robotics mental well-being Atomic and Molecular Physics and Optics machine learning quality of life Ecological Momentary Assessment (EMA) System integration Robot Artificial intelligence business |
| Zdroj: | Sensors Volume 21 Issue 20 Sensors (Basel, Switzerland) Sensors, Vol 21, Iss 6865, p 6865 (2021) |
| ISSN: | 1424-8220 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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