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Robotic-Based Well-Being Monitoring and Coaching System for the Elderly in Their Daily Activities
Francisco M Calatrava-Nicolás1, Eduardo Gutiérrez-Maestro2, Daniel Bautista-Salinas3
1ETSII (Escuela Técnica Superior de Ingeniería Industrial), Technical University of Cartagena, St. Dr. Fleming, s/n, 30203 Cartagena, Spain.
Sensors (Basel, Switzerland)
|October 26, 2021
Summary
This study introduces the RobWell system, using artificial intelligence for mood prediction and coaching to enhance elderly well-being. Preliminary results show progress in home automation and mood estimation, with ongoing research into robot navigation.
Area of Science:
- Robotics
- Artificial Intelligence
- Ambient Intelligence
- Gerontology
Background:
- The growing elderly population living alone faces isolation and psychological distress, exacerbated by events like the COVID-19 pandemic.
- There is a critical need for innovative healthcare solutions to support the well-being of seniors in their daily lives.
Purpose of the Study:
- To present the RobWell system, a robotic-based well-being monitoring and coaching system designed for the elderly.
- To outline the system's focus on artificial intelligence for mood prediction and coaching to improve mental well-being during daily activities.
Main Methods:
- Development of a system integrating ambient intelligence (sensors, actuators) with a robotic platform for user interaction.
- Implementation of machine learning algorithms for mood estimation using physiological signals.
- Setup and testing of a smart home environment with integrated sensors, actuators, and the robotic platform.
Main Results:
- Preliminary results demonstrate the feasibility of the home automation subsystem and mood estimation via machine learning.
- The ROS autonomous navigation stack and autodocking algorithm were found to be unreliable for the intended task.
- The robot's general autonomy was deemed sufficient, indicating potential for future development.
Conclusions:
- The RobWell system shows promise for improving the mental well-being of the elderly through AI-driven monitoring and coaching.
- Further research is needed to address challenges in autonomous robot navigation, exploring alternatives like semantic navigation, AI, and computer vision.
