Frequency-domain techniques for heart rate variability analysis

Xiangguo Yan, Chongxun Zheng
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引用次数: 3

Abstract

Two frequency domain techniques, fast Fourier transform (FFT) and maximum entropy estimation (MEE) methods for analyzing Heart Rate Variability (HRV), are described. Analysis results showed that low frequency components (LF:0.04-0.15 Hz) reflecting sympathetic nervous activity occupy a dominant position on day time, high frequency components (HF:0.4-0.40 Hz) reflecting vagal nervous activity become stronger at night. There is a cluster of peaks ranging from 0.20-0.30 Hz at night. In the morning, LF/HF ratio trend graphics changed sharply. This may be quite significant for predicting sudden death of an intensive heart disease patient. Both analysis results have a high degree of positive correlation, and cross-correlation coefficient is more than 0.99. However, MEE has a higher frequency resolution than FFT.
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心率变异性分析的频域技术
描述了两种频域技术,快速傅里叶变换(FFT)和最大熵估计(MEE)方法,用于分析心率变异性(HRV)。分析结果表明,反映交感神经活动的低频分量(LF:0.04 ~ 0.15 Hz)在白天占主导地位,反映迷走神经活动的高频分量(HF:0.4 ~ 0.40 Hz)在夜间增强。夜间有一组波峰在0.20-0.30 Hz之间。早盘,低高频比趋势图形变化剧烈。这对于预测重症心脏病患者的猝死可能具有重要意义。两种分析结果均具有高度正相关,相关系数均大于0.99。然而,MEE具有比FFT更高的频率分辨率。
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