西方音乐对人格类型的情感诱导,使用物联网技术技术
Dandan Ru1,2, Zhifang Wei3
1School of International Studies, Zhengzhou University, Zhengzhou, 450001, China.
Scientific reports
|November 27, 2025
概括
这项研究通过物联网 (IoT) 技术和电脑电图 (EEG) 情感识别来探索西方音乐对不同人格类型的情感影响. 贝塔和马节奏在分类情绪方面显示出最高的准确性.
科学领域:
- 神经科学是一个神经科学.
- 计算机科学 计算机科学
- 音乐心理学 音乐心理学
背景情况:
- 传统的音乐推算法无法解释人格驱动的情绪反应.
- 物联网 (IoT) 技术为通过音乐进行个性化情感诱导提供了新的途径.
- 基于脑电图 (EEG) 的情绪识别是一个新兴的领域,结合了情绪诱导,特征提取和模式识别.
研究的目的:
- 研究西方音乐对不同类型人格的情感诱导效应.
- 开发和评估基于EEG的情绪识别系统,利用物联网技术.
- 为了确定最佳的EEG节奏和分类器,以准确地识别音乐诱导状态中的情绪.
主要方法:
- 根据情感的维度模型,精选的西方音乐片段引发中性,积极和消极的情绪.
- 诱导了参与者经历三种不同的情绪状态的EEG信号.
- 分析了EEG特征,专注于β和节奏,并比较了各种分类器,如支持向量机 (SVM) 和委员会查询 (QBC).
主要成果:
- 贝塔和马节奏表现出最高的分类准确度 (分别为0.842和0.841) 对于情绪识别.
- 在所有受试者中观察到关键特征的电极位置分布一致.
- 支持矢量机 (SVM) 和委员会查询 (QBC) 实现了卓越的性能,平均正确率为94.7%和90.0%.
结论:
- 使用物联网技术的基于EEG的情绪识别可以有效地区分音乐诱导的情绪状态.
- 贝塔和马节奏对于精确地从EEG数据中分类情绪至关重要.
- SVM和QBC分类器为针对情感诱导的个性化音乐推系统提供了强大的性能.
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