Emotional condition in the Health Smart Homes environment: emotion recognition using ensemble of classifiers

Author(s)

Mano, Leandro Y. ; Yildirim, T ; Manolopoulos, Y ; Angelov, P ; Iliadis, L

• Document type: Journal article
• Source: 2018 INNOVATIONS IN INTELLIGENT SYSTEMS AND APPLICATIONS (INISTA); v. N/A, p. 8-pg., 2018-01-01.

Abstract

The fraction of elderly people in the population has increased significantly in most developed countries in recent years. Embedded computing enables the deployment of Health Smart Homes that can enhance nurses or caregivers to assist patients in need of timely help, and the implementation of this application can be extremely easy and cheap when aided by Internet of Things technologies. In addition, there are few studies that take into account the patient's emotional state, which is crucial for them to be able to recover from a disease. This article discusses the use of images and emotional detection to assist patients and elderly people within an in-home healthcare context and sets out a model for the classification of emotions based on the facial expressions of the users. Finally, the results described in this article show that the Ensemble Classification that is put forward can achieve greater rates of accuracy, average of 82,53%, in classifying feelings than what can be obtained by using a single classifier. (AU)

• FAPESP's process: 17/21054-2 - Combining Intelligence Artificial and Multimodal for Emotion Classification
• Grantee: Leandro Yukio Mano Alves
• Support Opportunities: Scholarships abroad - Research Internship - Doctorate
• FAPESP's process: 16/14267-7 - Exploiting the Internet of Things with Artificial Intelligence in the context of Health Smart Homes: a physical and emotional approach
• Grantee: Leandro Yukio Mano Alves
• Support Opportunities: Scholarships in Brazil - Doctorate