Emotional AI in Healthcare: a pilot architecture proposal to merge emotion recognition tools

Abstract

The use of emotional artificial intelligence (EAI) looks promising and is continuing to improve during the last years. However, in order to effectively use EAI to help in the diagnose and treat health conditions there are still significant challenges to be tackled. Because EAI is still under development, one of the most important challenges is to integrate the technology into the health provision process. In this sense, it is important to complement EAI technologies with expert supervision, and to provide health professionals with the necessary tools to make the best of EAI without a deep knowledge of the technology. The present work aims to provide an initial architecture proposal for making use of different available technologies for emotion recognition, where their combination could enhance emotion detection. The proposed architecture is based on an evolutionary approach so to be integrated in digital health ecosystems, so new modules can be easily integrated. In addition, internal data exchange utilizes Robot Operating System (ROS) syntax, so it can also be suitable for physical agents.