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The application of spectral analysis of electrocardiograms for valuation the condition of vehicles drivers

机译:心电图频谱分析在车辆驾驶员状态评估中的应用

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The paper is devoted to analysis of the heart rate variability using the cardiointervalogram of patients with bradycardia. As a result of the analysis we showed in our work that it is possible to detect the time-domain moment of the person's transition from the waking state to the state of sleep. This problem is rather actual for drivers of vehicles to prevent the car accidents. We suggested the special spectral coefficient “K”. It is ratio of the high frequency part of the signal spectral power to its low frequency part. We calculated the mean values of the coefficient “K” for patients with bradycardia. These values were lower than corresponding values for patients with normal heart rate. It is revealed, this coefficient decreases in the case of more strongly expressive bradycardia according to the expressiveness of a bradycardia. In our work we suggest to define threshold values of this coefficient for patients with different expressiveness of a bradycardia. Besides we consider spectral analysis of electrocardiosignal to determine heart arrhythmias. We suggest algorithm of analysis and original spectral parameter to discriminate normal QRS-complexes from pathological QRS-complexes. Boundary value of frequency separating a low-frequency part of a spectrum from high-frequency part was found experimentally.
机译:本文致力于使用心动过缓患者的心间隔图分析心率变异性。分析的结果表明,我们可以在工作中检测到​​人从清醒状态过渡到睡眠状态的时域矩。对于车辆驾驶员来说,这个问题是相当实际的,以防止发生车祸。我们建议使用特殊的频谱系数“ K”。它是信号频谱功率的高频部分与其低频部分的比率。我们计算了心动过缓患者的系数“ K”的平均值。这些值低于心率正常患者的相应值。揭示出,在表现更强的心动过缓的情况下,该系数根据心动过缓的表达而降低。在我们的工作中,我们建议为具有不同心动过缓表现的患者定义该系数的阈值。此外,我们考虑对心电信号进行频谱分析以确定心律不齐。我们建议使用分析算法和原始光谱参数来区分正常QRS络合物和病理QRS络合物。通过实验求出将频谱的低频部分与高频部分分离的频率的边界值。

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