Predicting Real Fear of Heights Using Virtual Reality

Autor: Valentina Tosto, Laura Anna Ripamonti, Dario Maggiorini, Giuseppe Boccignone, Davide Gadia
Rok vydání: 2021
Předmět:
Zdroj: GoodIT
Popis: Every year, in Europe alone, hundreds of workers die by falling from high height. This number could be greatly reduced by means of better training and quick detection of individuals with issues toward work at height. Workers proving to be less suited for the job can be subject to more intensive training or recruited for different positions. Unfortunately, the early detection of workers unsuited for working at height involves specialized personnel and expensive equipment to recreate a stressful environment. In this paper we propose a methodology to predict fear of heights by means of a virtual reality environment. We demonstrate that a 3D virtual environment is feasible for the prediction and give guidelines about meaningful physiological parameters useful for detection.
Databáze: OpenAIRE