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

Francisco M Calatrava-Nicolás,Inmaculada Méndez,Oscar Martínez Mozos,Francisco J Ortiz,Eduardo Gutiérrez-Maestro,Daniel Bautista-Salinas,Cecilia Ruiz-Esteban,Joaquín Roca González,José Alfonso Vera-Repullo,Manuel Jiménez-Buendía

doi:10.3390/s21206865

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.

Highlights

Scientific advances, in general terms, have improved living conditions as reflected in such basic aspects as longevity
The first experiment consists of splitting the dataset in two subsets, so that 75% of the samples are used for training and the remaining 25% are used for testing (Figure 11)
Starting with a smart home, the system was in operation for 21 days without failures with the devices connected continuously

Summary

Introduction

Scientific advances, in general terms, have improved living conditions as reflected in such basic aspects as longevity. There are expected to be around 125 million people over the age of 65 in the EU in 2030. According to the survey published by the INE (the Spanish National Institute of Statistics) 42.7% of women over the age of 85 lived alone, compared to 23.6% of men [3]. A clear example is the current COVID-19 pandemic, which has brought about social isolation with repercussions on mental health. INE statistics show that the number of people over 65 who lived alone in 2020 was 2,131,400 compared to 2,009,100 in 2019 [7], so that loneliness is already postulated as one of the main epidemics of the 21st century

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