Stress and anxiety are part of the human mental process which is often unavoidably yield by circumstances and situations such as waiting for a flight at the airport gate, hanging around before an exam, or while in an hospital waiting room. In this work we devise a decision system for a robotic aroma diffusion device designed to lessen stress and anxiety-related behaviors. The robot is intended as designed for deployments in closed environments that resembles the aspect and structure of a waiting room with different chairs where people sit and wait. The robot can be remotely driven by means of an artificial intelligence based on Radial Basis Function Neural Networks classifiers. The latter is responsible to recognize when stress or anxiety levels are arising so that the diffusion of specific aromas could relax the bystanders. We make use of thermal images to infer the level of stress by means of an ad hoc feature extraction approach. The system is prone to future improvements such as the refinement of the classification process also by means of accurate psychometric studies that could be based on standardized tests or derivatives.

Lessening stress and anxiety-related behaviors by means of AI-driven drones for aromatherapy

Capizzi G.;
2020-01-01

Abstract

Stress and anxiety are part of the human mental process which is often unavoidably yield by circumstances and situations such as waiting for a flight at the airport gate, hanging around before an exam, or while in an hospital waiting room. In this work we devise a decision system for a robotic aroma diffusion device designed to lessen stress and anxiety-related behaviors. The robot is intended as designed for deployments in closed environments that resembles the aspect and structure of a waiting room with different chairs where people sit and wait. The robot can be remotely driven by means of an artificial intelligence based on Radial Basis Function Neural Networks classifiers. The latter is responsible to recognize when stress or anxiety levels are arising so that the diffusion of specific aromas could relax the bystanders. We make use of thermal images to infer the level of stress by means of an ad hoc feature extraction approach. The system is prone to future improvements such as the refinement of the classification process also by means of accurate psychometric studies that could be based on standardized tests or derivatives.
2020
Artificial Intelligence
Feature Extraction
Human Machine Interaction
Neural Networks
Robotics
Social Psychology
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/503725
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