Fast and Accurate Power Spectral Analysis of Heart Rate Variability using Fast Gaussian Gridding

Charalampos Eleftheriadis, G. Karakonstantis
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引用次数: 1

Abstract

In this paper, we propose an algorithm for fast and accurate Power Spectral Analysis of Heart Rate Variability based on the Lomb Periodogram. The previously introduced Fast-Lomb periodogram, may have reduced the computational complexity of PSA, however it still requires a large oversampling factor, which increases the complexity of the needed FFTs. In our approach, by utilising the Fast Gaussian Gridding method we produce accurate evenly spaced grids for the required FFTs by restricting the oversampling factor only to 2. By doing so, the required FFT size is reduced by up to 4 times without compromising the output accuracy. Our results indicate that the proposed spectral analysis system can achieve upto 76.55% savings in the number of operations or up-to 75.8% in terms of the total execution time.
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基于快速高斯网格的心率变异性快速准确功率谱分析
本文提出了一种基于Lomb周期图的快速准确的心率变异性功率谱分析算法。先前引入的Fast-Lomb周期图可能降低了PSA的计算复杂度,但它仍然需要很大的过采样因子,这增加了所需fft的复杂性。在我们的方法中,通过利用快速高斯网格方法,我们通过限制过采样因子仅为2,为所需的fft生成精确的均匀间隔网格。通过这样做,所需的FFT大小减少了多达4倍,而不影响输出精度。我们的结果表明,所提出的频谱分析系统可以实现高达76.55%的操作次数节省或高达75.8%的总执行时间。
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