图像唤起的情绪识别听力受损对象用EEG信号的听力受损对象
Mu Zhu1, Haonan Jin1, Zhongli Bai1
1Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems, School of Electrical Engineering and Automation, Tianjin University of Technology, Tianjin 300384, China.
Sensors (Basel, Switzerland)
|July 8, 2023
概括
这项研究引入了一种新的多轴自我注意模型,用于使用电脑电图 (EEG) 信号识别听力障碍者的情绪识别. 这种先进的模型与传统方法相比显示出更高的性能,提高了情绪分类的准确性.
科学领域:
- 神经科学是一个神经科学.
- 人工智能的人工智能
- 生物医学工程 生物医学工程
背景情况:
- 通过电脑电图 (EEG) 信号识别情绪正在获得引力.
- 听力受损的个体可能会表现出明显的信息处理偏见.
- 了解这一群体的情绪反应对于沟通至关重要.
研究的目的:
- 开发和评估基于EEG的高级情绪识别模型,用于听力障碍者.
- 为了比较听力受损和非听力受损受试者之间的模型性能.
- 为了研究大脑地形图,在情绪处理中的差异.
主要方法:
- 从听力受损和无听力受损的参与者收集了EEG数据,观看了情感面孔.
- 从原始信号和微分 (DE) 中使用对称差异和分数提取空间特征.
- 提出了一个多轴自我注意力分类模型,将本地和全球注意力与卷积整合起来.
主要成果:
- 拟议的多轴自我注意模型的表现优于原始特征方法.
- 多功能融合在两组受试者中都表现出有效性.
- 听力受损者达到70.2% (3级) 和50.15% (5级) 的平均准确率,无听力受损者达到72.05% (3级) 和51.53% (5级) 的平均准确率.
- 在听力受损受试者中确定了独特的歧视性大脑区域,包括叶.
结论:
- 新的自我注意模型显著改善了基于EEG的情绪识别,特别是在听力障碍者身上.
- 多功能融合提高了分类准确性.
- 大脑拓分析揭示了听力受损人口中独特的情绪处理模式.
相关概念视频
01:17Auditory Perception
The auditory system is essential for sound perception, utilizing various critical structures. When sound waves enter the outer ear, they travel through the ear canal and cause the eardrum to vibrate. These vibrations are then transmitted to the middle ear, where three tiny bones – the malleus, incus, and stapes – amplify the sound. This amplification is crucial, as it ensures that the sound vibrations are strong enough to be conveyed to the inner ear. These vibrations then reach the cochlea, a...
01:20Labeling Emotion
Emotional labeling is a cognitive process that involves identifying and naming one's emotions, such as anger, fear, happiness, or sadness. It allows individuals to recognize and express their internal emotional states, a critical aspect of emotional regulation and communication. Labeling emotions requires more than mere recognition; it also involves drawing upon memory and contextual cues to understand the current situation and apply a corresponding emotional label. For instance, feeling...