TY - JOUR
TI - Participant Modeling: The Use of a Guided Master in the Modern World of Virtual Reality Exposure Therapy Targeting Fear of Heights
AU - Caravas, P.
AU - Kritikos, J.
AU - Alevizopoulos, G.
AU - Koutsouris, D.
JO - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
PY - 2021
VL - 376 LNICST
TODO - null
SP - 161-174
PB - Springer Science and Business Media Deutschland GmbH
SN - null
TODO - 10.1007/978-3-030-76066-3_13
TODO - Motion estimation;  Patient treatment;  Wearable technology, Common denominators;  Immersive virtual reality;  Mental health;  Motion recognition;  Rating scale;  Treatment quality;  Virtual reality exposure therapies;  VR systems, Virtual reality
TODO - With the percentage of mental health disorders on the rise and the cost for their treatment reaching astounding proportions, research in their treatment has also become quite extensive. Individuals suffering from the effects of their disorder constituting them incapable at various levels to lead a normal life, the need for a more effective treatment has been well established. We have focused on anxiety disorders specifically, which have mainly fear as their common denominator, and using this we decided to look into the role of the clinician in live ET sessions so as to examine whether this role can be replicated in a VRET simulation with similar or better outcomes for the patient, i.e. a more effective treatment. Our hypothesis was tested in an outpatient setting with patients being separated into two groups. We examined whether the presence of a virtual guided master using participant modeling in a virtual environment was as effective or more effective than the Standard ET method. Our VR system is based on the Full Body Immersive Virtual Reality System with Motion Recognition Camera created by Jacob Kritikos. The outcomes were gathered via the Session Rating Scale by Miller which led to the conclusion that participant modeling within a VRET approach can lead to a better treatment quality. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.
ER -