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Comparison of the Use of Blink Rate and Blink Rate Variability for Mental State Recognition

机译:使用眨眼率和眨眼率变异性进行心理状态识别的比较

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摘要

Recent research has unearthed that blink rate variability (BRV) can be employed as a psychophysiological measure. However, its efficiency for mental state recognition (MSR) has not been investigated yet. Because BRV can indicate dynamics inherent in eye blinks, we conjectured that BRV might exhibit stronger abilities for the MSR if compared with blink rate (BR), known as the leading indicator derived from eye blinks for MSR. Therefore, in this paper, we attempted to differentiate between high and low cognitive loads of an individual through the analyses of BR and BRV, respectively, which could be viewed as a preliminary study for comparing their MSR abilities. First, an n-back experiment was performed to collect data. Then, in order to characterize the phenomenon of BRV, the features were extracted from its time and frequency domains, respectively. Finally, the area under the curve (AUC) values of BRV and BR for MSR were estimated by the ten commonly used classifiers, respectively. The results indicated that BRV achieves significantly higher AUC values than BR, which suggests its strong potentiality for MSR. In sum, the BRV may prove to be a promising method for the MSR, which should be considered in the future.
机译:最近的研究发现,眨眼频率变异性(BRV)可以用作心理生理指标。但是,尚未对其精神状态识别(MSR)的效率进行研究。由于BRV可以指示眨眼固有的动力学特性,因此我们推测,与眨眼率(BR)相比,BRV可能表现出更强的MSR能力。因此,在本文中,我们试图通过对BR和BRV的分析来区分个人的高认知负荷和低认知负荷,这可被视为比较其MSR能力的初步研究。首先,进行了一次n-back实验以收集数据。然后,为了表征BRV现象,分别从其时域和频域中提取了特征。最后,分别通过十个常用分类器来估算MSR的BRV和BR的曲线下面积(AUC)值。结果表明BRV的AUC值明显高于BR,这表明其具有强大的MSR潜力。总而言之,BRV可能被证明是MSR的一种有前途的方法,将来应该考虑使用。

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