Moving from VR into AR using Bio-Cybernetic Loops and Physiological Sensory Devices for Intervention on Anxiety Disorders

Abstract

Anxiety disorders comprise different clinical conditions that affect individuals in their personal, professional and social domains. The development of new intervention approaches for the treatment of anxiety disorders is crucial. As a step forward into promoting the well-being through adaptive physiological responses, we developed an Augmented Reality (AR) based system using bio-cybernetic loops to create an adaptive system for exposure therapy in anxiety disorders. The system was built using open source software (e.g., NyARToolkit, and Unity 3D). AR technology uses computer-generated information to enrich the real world. It can be used with less intrusive devices to collect physiological data (e.g., Bitalino) describing human behavior in a cycle. In this context our research project aims to study behavior during exposure to biologically relevant stimuli such as snakes. Phobia is described as an irrational fear to an object/stimulus. This fear triggers several physiological responses from sensors as increased heart rate (ECG) and skin conductance (EDA), which are responses from the autonomous nervous system. This approach can be used in several sessions, where the system through machine learning algorithms adapts the tresholds to the individual profile of each participant from historical data. Our study has been carried out in two stages: (1) The participants in a total of 35 students (30 males and 5 females with ages ranging from 19 to 29 years) were invited to fill a snake questionnaire (SNAQ). (2) A sub-sample was enrolled in an exposure session in AR using a virtual snake while collecting psychophysiological responses from sensors data. The results have shown increased physiological responses in two AR exposure sessions using snakes as stimuli. Therefore we conclude that the system was efficient to detect changes in physiological responses during the exposure sessions.

Anxiety disorders comprise different clinical conditions that affect individuals in their personal, professional and social domains. The development of new intervention approaches for the treatment of anxiety disorders is crucial. As a step forward into promoting the well-being through adaptive physiological responses, we developed an augmented reality (AR)-based system using bio-cybernetic loops to create an adaptive system for exposure therapy in anxiety disorders. The system was built using open-source software (e.g., NyARToolkit and Unity 3D). AR technology uses computer-generated information to enrich the real world. It can be used with less intrusive devices to collect physiological data (e.g., Bitalino) describing human behavior in a cycle. In this context, our research project aims to study behavior during exposure to biologically relevant stimuli such as snakes. Phobia is described as an irrational fear to an object/stimulus. This fear triggers several physiological responses from sensors as increased heart rate (ECG) and skin conductance (EDA), which are responses from the autonomous nervous system. This approach can be used in several sessions, where the system through machine learning algorithms adapts the thresholds to the individual profile of each participant from historical data. Our study has been carried out in two stages: (1) The participants in a total of 35 students (30 males and 5 females with ages ranging from 19 to 29 years) were invited to fill a snake questionnaire (SNAQ). (2) A subsample was enrolled in an exposure session in AR using a virtual snake while collecting psychophysiological responses from sensors data. The results have shown increased physiological responses in two AR exposure sessions using snakes as stimuli. Therefore we conclude that the system was efficient to detect changes in physiological responses during the exposure sessions.