使用生物传感器在虚拟现实中的焦虑分类:一个迷你范围审查
Deniz Mevlevioğlu1, Sabin Tabirca1,2, David Murphy1
1Department of Computer Science, University College Cork, Cork, Ireland.
PloS one
|July 10, 2023
概括
在虚拟现实 (VR) 中,使用生物传感器和机器学习,高准确度地预测焦虑. 然而,缺乏标准化的焦虑定义和小样本大小限制了目前的研究结果.
科学领域:
- 人与计算机的交互
- 计算神经科学是一种神经科学.
- 心理生理学 心理生理学
背景情况:
- 焦虑预测模型可以增强虚拟现实 (VR) 应用.
- 在VR环境中评估准确的焦虑分类证据至关重要.
研究的目的:
- 在虚拟现实中对调查焦虑分类的研究进行范围审查.
- 评估用于VR中焦虑检测的机器学习模型的准确性和方法.
主要方法:
- 对2010-2022年同行评审研究的范围审查.
- 在Scopus,科学网,IEEE Xplore和ACM数字图书馆进行了搜索.
- 包括使用机器学习和生物传感器在VR中评估焦虑的研究.
主要成果:
- 从1749个记录中选择了11项研究 (n=237).
- 两个输出模型的准确性在75%到96.4%之间.
- 电皮活动和心率是常见的生物传感器.
结论:
- 在VR中,高精度的实时焦虑检测是可行的.
- 缺乏标准化的焦虑基础真相和小,学生偏见的样本阻碍了解释.
- 未来的研究需要明确的焦虑定义,更大的/多样化的样本和纵向研究.
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