论文标题
基于玩家的心理生理数据，在虚拟现实游戏中对模拟器疾病的实时检测
Real-Time Detection of Simulator Sickness in Virtual Reality Games Based on Players' Psychophysiological Data during Gameplay
论文作者
论文摘要
在过去的十年中，虚拟现实（VR）技术一直在增殖，尤其是在过去的几年中。但是，模拟器疾病（SS）仍然是其更广泛采用的重要问题。当前，检测SS的最常见方法是使用模拟器疾病问卷（SSQ）。 SSQ是一种主观的测量，并且不足以实时应用程序（例如VR游戏）。这项研究旨在调查如何使用机器学习技术在VR游戏游戏游戏中根据游戏中的角色和用户的生理数据来检测SS。为了实现这一目标，我们设计了一个实验，以三种类型的游戏收集此类数据。我们培训了一个长期的短期记忆神经网络，并具有数据集的眼睛跟踪和角色移动数据，以实时检测SS。我们的结果表明，在VR游戏中，我们的模型是实时检测SS的准确有效方法。
Virtual Reality (VR) technology has been proliferating in the last decade, especially in the last few years. However, Simulator Sickness (SS) still represents a significant problem for its wider adoption. Currently, the most common way to detect SS is using the Simulator Sickness Questionnaire (SSQ). SSQ is a subjective measurement and is inadequate for real-time applications such as VR games. This research aims to investigate how to use machine learning techniques to detect SS based on in-game characters' and users' physiological data during gameplay in VR games. To achieve this, we designed an experiment to collect such data with three types of games. We trained a Long Short-Term Memory neural network with the dataset eye-tracking and character movement data to detect SS in real-time. Our results indicate that, in VR games, our model is an accurate and efficient way to detect SS in real-time.
