Feasibility of emotion recognition from breath gas information
Feasibility of emotion recognition from breath gas information
复制标题
从呼吸气体信息进行情绪识别的可行性
DOI：
10.1109/aim.2008.4601732
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发表时间：
2008
期刊：
影响因子：
--
通讯作者：
I. Sugimoto
中科院分区：
文献类型：
--
作者：
K. Takahashi;I. Sugimoto
本文提出了一种智能气体传感系统，利用呼吸气体信息实现情绪识别。设计了一种呼吸气体传感系统，采用带有等离子体聚合物薄膜的石英晶体谐振器作为传感器。为了收集情绪状态下的呼吸气体数据，利用牙齿上升来激发情绪进行心理实验。在情感识别的计算实验中，考虑了舒适和无情感两种情感，并研究了基于机器学习的方法，例如人工神经网络（ANN）和支持向量机（SVM）。使用 ANN 获得的平均情绪识别率为 47.5%，使用 SVM 获得的平均情绪识别率为 67.5%。实验结果表明，使用呼吸气体信息是可行的，并且基于机器学习的方法非常适合这项任务。
This paper proposes a smart gas sensing system to achieve emotion recognition using breath gas information. A breath gas sensing system is designed by using a quartz crystal resonator with a plasma-polymer film as a sensor. To collect breath gas data under emotional state, psychological experiments are carried out using a dental rise to excite emotions. In computational experiment of emotion recognition, two emotions of comfortableness and no emotion are considered and the machine learning-based approach such as an artificial neural network (ANN) and a support vector machine (SVM) is investigated. The obtained average emotion recognition rates are 47.5% using the ANN and 67.5% using the SVM, respectively. Experimental results show that using breath gas information is feasible and the machine learning-based approach is well suited for this task.