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Understanding the Effect of a Motivational Music on Indian Male Volunteers Using Recurrence Analysis and ANN Classification

机译:通过递归分析和ANN分类了解动机音乐对印度男性志愿者的影响

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This paper presents a framework to explore the effect of music (motivational song) on cardiac physiology using recurrence analysis. For the characterization of the ECG signals, recurrence has been reported to be an effective tool. This non-linear dynamic method has been considered economical than other computational methods. The ECG data were acquired from eighteen male volunteers. The signals were further processed to extract the R-R intervals (RRI). Recurrence analysis of the ECG and the RRI signals suggested a reduction in the isometric recurrence in the post-stimulus condition, and hence, a corresponding increase in the heart rate variability. The variation was also evidenced from the ANN classification of the ECG and the RRI signals with efficiency of ≥ 85%.
机译:本文提出了一个框架,通过递归分析来探索音乐(激励性歌曲)对心脏生理的影响。为了表征ECG信号,据报道复发是一种有效的工具。这种非线性动态方法被认为比其他计算方法更经济。心电图数据来自18名男性志愿者。进一步处理信号以提取R-R间隔(RRI)。对ECG和RRI信号的复发分析表明,刺激后条件下等距复发的减少,因此心率变异性相应增加。从心电图和RRI信号的ANN分类中也可以证明这种变化,效率≥85%。

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