基于心脏信号的情绪自动分类:一个系统的文献评论
Anderson Faria Claret1, Karina Rabello Casali1, Tatiana Sousa Cunha2
1Institute of Science and Technology, Federal University of São Paulo, São José dos Campos, Brazil.
Annals of biomedical engineering
|August 5, 2023
概括
这项研究回顾了用于情绪识别的心脏信号分析,发现低成本的可穿戴传感器对准确和可访问的情绪状态检测有希望. 进一步的研究可以指导这些情绪识别系统的发展.
科学领域:
- 情感计算是一种情感计算.
- 生物医学信号处理
- 人与计算机的互动.
背景情况:
- 情绪显著影响人类的认知和日常生活.
- 人工智能/ML的进步推动了人们对自动化情绪识别的兴趣.
- 由于影响因素和生理变化,准确识别情绪是具有挑战性的.
研究的目的:
- 通过心脏信号进行情绪检测,识别和分类的系统文献审查 (SLR).
- 调查信号采集,特征提取,诱导和分类方法的当前趋势.
- 评估使用低成本可穿戴传感器用于情绪识别的可行性.
主要方法:
- 在四个研究数据库中进行了系统文献审查 (SLR).
- 分析了27篇符合选择标准的文章.
- 审查的重点是心脏信号采集,特征提取,情绪诱导和分类技术.
主要成果:
- 来自低成本可穿戴设备的心脏信号显示了情绪识别的可行性.
- 确定了各种情绪诱导方法和自动分类算法.
- 仅基于心脏信号的情绪识别的关键挑战得到了强调.
结论:
- 该研究提供了对开发自动情绪识别应用程序的技术的见解.
- 它强调了用于心脏信号采集的低成本,可穿戴和不引人注目的设备的重要性.
- 通过生理信号分析,研究结果支持通过生理信号分析进行准确和可访问的情绪识别.
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