Concurrent PTSD Psychotherapy Through Multi-Personnel Virtual Reality Framework
DOI:
https://doi.org/10.37591/rrjon.v7i1.968Abstract
Networked Virtual Environments (NEV) are sets of disjointed virtual worlds which are topographically set apart from the users yet connected through the communication network to give them the illusion of being in the same virtual location. NVEs are increasingly receiving consideration from business and research point of view. Contrasted with various sorts of possible applications, NVEs require a high responsiveness to ensure continuous streaming of live data for full immersion. As virtual reality has gained wide attention in therapy for posttraumatic stress disorder (PTSD), which on a quantitative scales accounts for 20% of veterans returning from the war. Here, soldiers suffers from traumatic and extreme experience of violence where there attention and vigilance is constantly to to deal with unpredictable threats and an unprecedented number of loss of fellow soldiers. The idea here is to avail psychotherapy to the soldiers in multiple concurrent sessions with their fellow soldiers to cope up with the experience. It is as yet difficult to develop such applications since it require to create virtual reality framework over distributed databases; as every user needs locally adequate data flow to concurrently construct a scene as with other users and able to accommodate multi-user interactions in the virtual environment. Such information requires simultaneous computation and communication of streaming data. In this study we built up a prototype of a NVE in view of the blend of Minority Game (MG) and Online Induction Algorithm (OIA) with lossless transfer functions and perform a series of concurrent PTSD psychotherapy over multiple PTSD subjects.
Keywords: PTSD psychotherapy, networked virtual environments, online learning, data stream control, adaptive networking
Cite this Article
Ankush Rai. Concurrent PTSD Psychotherapy Through Multi-Personnel Virtual Reality Framework. Research & Reviews: Journal of Neuroscience. 2017; 7(1): 22–26p.
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