Liu Xinyu, Shan Yuhao, Peng Min, Chen Huanyu, Chen Tong
Chongqing Key Laboratory of Non-Linear Circuit and Intelligent Information Processing, Southwest University, Chongqing 400715, China.
School of Electronic and Information Engineering, Southwest University, Chongqing 400715, China.
Entropy (Basel). 2020 Aug 31;22(9):962. doi: 10.3390/e22090962.
Emotional and physical stress can cause various health problems. In this paper, we used tissue blood oxygen saturation (StO2), a newly proposed physiological signal, to classify the human stress. We firstly constructed a public StO2 database including 42 volunteers subjected to two types of stress. During the physical stress experiment, we observed that the facial StO2 right after the stress can be either increased or decreased comparing to the baseline. We investigated the StO2 feature combinations for the classification and found that the average StO2 values from left cheek, chin, and the middle of the eyebrow can provide the highest classification rate of 95.56%. Comparison with other stress classification method shows that StO2 based method can provide best classification performance with lowest feature dimension. These results suggest that facial StO2 can be used as a promising features to identify stress states, including emotional and physical stress.
情绪和身体压力会引发各种健康问题。在本文中,我们使用组织血氧饱和度(StO2)这一最新提出的生理信号来对人类压力进行分类。我们首先构建了一个公共的StO2数据库,其中包括42名经历两种压力类型的志愿者。在身体压力实验中,我们观察到压力施加后脸部的StO2与基线相比可能会升高或降低。我们研究了用于分类的StO2特征组合,发现左脸颊、下巴和眉中部的平均StO2值能提供最高95.56%的分类率。与其他压力分类方法的比较表明,基于StO2的方法能以最低的特征维度提供最佳的分类性能。这些结果表明,脸部StO2可作为一种有前景的特征来识别压力状态,包括情绪和身体压力。