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Can potentials of unbalanced complex kinetics of heart rate variability estimate drowsiness?

机译:心率变异性不平衡复杂动力学的潜力可以估计睡意吗?

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Several investigations have shown that most traffic accidents are due to drowsy driving. Much research has been carried out to address this issue. The authors of one study were able to measure the drivers' heart rate variability and estimate their drowsiness. In this study, we investigated the relationship between the drowsiness and physiological condition of the drive in the driving simulator environment by quantifying autonomic nervous system activity using “potentials of unbalanced complex kinetics” (PUCK) analysis of heart rate variability and conventional frequency-domain analysis using the Karolinska sleepiness scale (KSS). Both frequency-domain and PUCK parameter values had significant statistical differences for almost all subjects in relation to drowsiness: no drowsiness (mean KSS scores <; 5.5), light drowsiness (KSS scores > 5.5 and <; 7.5), and heavy drowsiness (>7.5). Furthermore, the classification ability of PUCK analysis was superior to that of frequency-domain analysis. Therefore, PUCK analysis of heart rate variability may be useful for assessing drowsiness while driving.
机译:多项调查表明,大多数交通事故是由于昏昏欲睡的驾驶所致。为了解决这个问题已经进行了许多研究。一项研究的作者能够测量驾驶员的心率变异性并估计他们的困倦程度。在这项研究中,我们通过使用心率变异性的“不平衡复杂动力学势”(PUCK)分析和常规频域分析来量化自主神经系统活动,从而研究了驾驶模拟器环境中驾驶员睡意与生理状况之间的关系。使用Karolinska嗜睡量表(KSS)。对于睡意,几乎所有受试者的频域和PUCK参数值均具有显着的统计学差异:无睡意(平均KSS得分<; 5.5),轻睡意(KSS得分> 5.5和<; 7.5)和沉睡(> 7.5)。此外,PUCK分析的分类能力优于频域分析。因此,对心率变异性进行PUCK分析可能有助于评估驾驶时的睡意状况。

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