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相关概念视频

Empathy02:34

Empathy

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Some researchers suggest that altruism operates on empathy. Empathy is the capacity to understand another person’s perspective, to feel what he or she feels. An empathetic person makes an emotional connection with others and feels compelled to help (Batson, 1991). Empathy can be expressed in several ways, including cognitive, affective, and motor. 
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相关实验视频

Updated: Jan 16, 2026

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
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使用传感器数据和机器学习在VR会议期间预测同情心和其他心理状态.

Emilija Kizhevska1,2, Hristijan Gjoreski3,4, Mitja Luštrek1,2

  • 1Institut "Jožef Stefan", 1000 Ljubljana, Slovenia.

Sensors (Basel, Switzerland)
|September 27, 2025
PubMed
概括
此摘要是机器生成的。

虚拟现实 (VR) 通过使用机器学习模型来预测用户从生理信号的同理心水平来增强同理心评估. 这项研究提供了一个新的方法来客观地测量同情心,补充了传统的自我报告方法.

关键词:
同理心同理心同情心机器学习是机器学习.精神状态 精神状态 精神状态传感器数据 传感器数据虚拟现实 虚拟现实 虚拟现实 虚拟现实

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Virtual Reality Experiments with Physiological Measures
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Last Updated: Jan 16, 2026

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科学领域:

  • 心理学和认知科学 心理学和认知科学
  • 人与计算机的交互
  • 机器学习应用 机器学习应用

背景情况:

  • 虚拟现实 (VR) 被认为具有潜力通过让用户沉浸在不同的视角中来培养同情心.
  • 目前的同理心评估方法缺乏通用标准,需要创新的方法.
  • 在VR体验期间的生理反应为客观的同理心测量提供了潜在的途径.

研究的目的:

  • 为了研究自我报告的同理心水平和VR暴露期间的生理反应之间的关系.
  • 开发和评估机器学习模型,以使用生理数据预测状态和特征同理心.
  • 引入一套新的VR视频数据集,旨在引起对研究和临床使用的同情.

主要方法:

  • 105名参与者体验了3D 360° VR视频,这些视频描绘了演员表达各种情绪.
  • 共感水平通过自我报告问卷进行评估.
  • 使用传感器记录生理信号,并使用机器学习模型 (随机森林) 进行预测.

主要成果:

  • 随机森林模型准确地预测了特征同理心 (9.1%的MAPE) 和分类状态同理心 (67%的平衡准确度).
  • 预测模型是为非同情激发 (78%准确率) 和区分同情与非同情激发 (79%准确率) 开发的.
  • 统计分析探讨了叙事背景,性别和情感对同情感的影响.

结论:

  • 利用生理信号的机器学习模型提供了一个客观而有效的方法来预测VR期间的同情度.
  • 这项研究提供了有价值的数据集和预测工具,以推进同理心研究和临床应用.
  • 基于VR的生理监测显示出作为传统同理心评估的补充方法的希望.