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首页> 外文期刊>Computer Methods and Programs in Biomedicine: An International Journal Devoted to the Development, Implementation and Exchange of Computing Methodology and Software Systems in Biomedical Research and Medical Practice >Increasing sensitivity in the measurement of heart rate variability: The method of non-stationary RR time-frequency analysis
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Increasing sensitivity in the measurement of heart rate variability: The method of non-stationary RR time-frequency analysis

机译：测量心率变异性的敏感性增加：非平稳RR时频分析方法

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A novel method of the time-frequency analysis of non-stationary heart rate variability (HRV) is developed which introduces the fragmentary spectrum as a measure that brings together the frequency content, timing and duration of HRV segments. The fragmentary spectrum is calculated by the similar basis function algorithm. This numerical tool of the time to frequency and frequency to time Fourier transformations accepts both uniform and non-uniform sampling intervals, and is applicable to signal segments of arbitrary length. Once the fragmentary spectrum is calculated, the inverse transform recovers the original signal and reveals accuracy of spectral estimates. Numerical experiments show that discontinuities at the boundaries of the succession of inter-beat intervals can cause unacceptable distortions of the spectral estimates. We have developed a measure that we call the " RR deltagram" as a form of the HRV data that minimises spectral errors. The analysis of the experimental HRV data from real-life and controlled breathing conditions suggests transient oscillatory components as functionally meaningful elements of highly complex and irregular patterns of HRV.
机译：开发了一种新的非平稳心率变异性（HRV）时频分析方法，该方法引入了碎片频谱作为一种度量，将HRV段的频率内容，时间和持续时间结合在一起。碎片光谱是通过类似的基函数算法计算的。频率到时间和频率到时间傅立叶变换的这种数值工具可以接受均匀和不均匀的采样间隔，并且适用于任意长度的信号段。一旦计算了碎片频谱，逆变换将恢复原始信号并揭示频谱估计的准确性。数值实验表明，连续心跳间隔的边界处的不连续性会引起频谱估计值的不可接受的失真。我们已经开发出一种称为“ RR deltagram”的量度，作为最小化频谱误差的HRV数据形式。对现实生活中和控制呼吸条件下的HRV实验数据的分析表明，短暂振荡成分是HRV高度复杂和不规则模式的功能上有意义的元素。

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