Visual analysis system to detect and predict the signs of anxiety in healthcare

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The intention of this project is to identify non-verbal cues of anxiety in dental practice. This project uses the dental practice as an example of a stressful health environment. The aim of this project is to analyse the action and behaviour of dental patients through videos to predict and detect their level of anxiety. The framework of this project is based on a deep learning approach to analyse the movement and body actions of dental patients. This flow is based on video processing techniques for action recognition. The main lines of this research study can be summarised as follows: 1) Updating the current literature review on visual analysis systems on behaviour expression and action prediction 2) Identify the appropriate machine vision approach to detect and predict anxiety to be expanded 3) Improve the framework to perform efficiently in real time and in real-world scenarios. 4) Implement the developed system and perform experiments in dental practice simulations.