A Low-Cost Cognitive Assistant

Abstract

In this paper, we present in depth the hardware components of a low-cost cognitive assistant. The aim is to detect the performance and the emotional state that elderly people present when performing exercises. Physical and cognitive exercises are a proven way of keeping elderly people active, healthy, and happy. Our goal is to bring to people that are at their homes (or in unsupervised places) an assistant that motivates them to perform exercises and, concurrently, monitor them, observing their physical and emotional responses. We focus on the hardware parts and the deep learning models so that they can be reproduced by others. The platform is being tested at an elderly people care facility, and validation is in process.

Machine Learning Techniques for Assistive Robotics

“…In Reference [4], a system to detect the performance and the emotional state that elderly people have when performing exercises is presented. With this detection, the authors want to build an assistant that motivates those people to perform exercises and, concurrently, monitors them, observing their physical and emotional responses.…”

I2E: A Cognitive Architecture Based on Emotions for Assistive Robotics Applications

“…Marceddu in [8] adopted machine learning techniques to analyze the passengers' emotions while driving with alternative vehicle calibrations; through the analysis of these emotions, it was possible to obtain an objective metric about the comfort feeling of the passengers. Rincon in [9] presented a low-cost cognitive assistant. The aim was to detect the performance and the emotional state that older people present when performing exercises.…”