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The Adjusted Reality Vision - Emerging Technology for Digital Transformation of Disruptive Environmental Stimuli.

Authors :
Beyer-Wunsch, P.
Reichert, M.
Pryss, R.
Source :
Procedia Computer Science; 2022, Vol. 210, p157-164, 8p
Publication Year :
2022

Abstract

Through a novel approach, which we call Adjusted Reality, it should become possible to virtually adapt physical reality by shrinking it virtually. You could also call it the reverse approach of Augmented Reality (AR). We see the main application in the medical field, for example with Highly Sensitive Persons (HSP). These individuals experience immense sensory and psychological overload. Due to the stressful situations caused by the disruptive stimuli, mental illnesses such as depression, anxiety disorders or somatoform disorders can develop and manifest. Up to now, there are only a few possibilities to offer help to these persons and thus prevent the symptoms. Therapies or participation in self-help groups can be mentioned as means of help. Interestingly, there are no digital aids for HSP so far, neither wearables nor mobile applications. By using Adjusted Reality, the aforementioned consequences should at best be avoided, or at least mitigated, by reducing the physical stimuli before they reach the sensory cells. The functionality of Adjusted Reality is therefore designed as an intelligent, AI-assisted and multimodal wearable system. Sensory input is personalized in the system, digitally modified, and delivered in an attenuated version to the sensory cells and finally to the brain. Through the use of Adjusted Reality, individuals are expected to relax and feel more comfortable with themselves, including their situation within society. In general, due to its omnipotent possibilities, Adjusted Reality can be relevant whenever physical experiences can be specifically reduced. In this work, these possibilities will be further explored. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
18770509
Volume :
210
Database :
Supplemental Index
Journal :
Procedia Computer Science
Publication Type :
Academic Journal
Accession number :
160212634
Full Text :
https://doi.org/10.1016/j.procs.2022.10.132