i-RISE: An IoT-based Semi-Immersive Affective monitoring framework for Anxiety Disorders

The increasing trend of using wearable sensors for monitoring various physiological signals has helped researchers to advance the research in the development and application of wearable computing systems. In addition to having an active lifestyle, the emotional well-being of a person is important in maintaining a healthier balanced life. With the application of affective computing, also known as artificial emotional intelligence, in wearable computing, devices and systems can recognize, interpret and simulate human emotions. In this research, we propose a cost-effective semi-immersive affective monitoring system that can help in analyzing emotion features for monitoring anxiety disorders by monitoring physiological signals of the user and aid in emotion elicitation through a semi-immersive environment. The proposed system, i-RISE, was used to evaluate the role of ambient sensing in detecting anxiety. The system was validated by using user input to record their emotions. A correlation between the user input and anxiety detected using the bayesian network yielded an accuracy of 90.23