arXiv:2606.26816cs.AI2026-06

分析40名健康人的心率变异性,找出最可靠指标提升临床应用价值。

Computational Analysis of Heart Rate Variability in Healthy Adults

  • 用计算方法分析时域、频域和非线性指标,评估其正态性与稳定性。
  • 发现多数指标稳定,但高频相关指标重复性差,仅需一个即可。
  • 推荐使用ApEn、HRVi等5个指标,适合临床研究和跨研究比较。

心率变异性(HRV)是评估心脏生理状态的重要指标,有助于疾病诊断。然而,健康人群的HRV参数研究仍有限,且缺乏金标准。本研究对40名健康成年人(20名男性,20名女性,年龄30-50岁)进行HRV分析,采用计算信号处理与数据分析方法,评估时间、频率和非线性指标的五个核心问题:正态性、稳定性、相关性、可重复性和一致性。主要发现:(1) 时域和非线性指标(尤其是全局和低频[LF])呈正态分布,存在性别差异;(2) 多数指标稳定,但高频[HF]相关指标除外;(3) HF相关指标间高度相关,表明在研究中只需保留一个;(4) 与Fantasia数据库对比显示,大多数指标误差低于10%,但女性的SD2和SDNN误差超过15%;(5) 时域和非线性指标的组间变异小,而频域指标变异大,限制了跨研究比较。推荐的指标包括ApEn和IRR(全局变异性)、HRVi和SD2(LF)、MADRR或rMSSD(HF),这些指标能更准确反映HRV特征,提升其临床与研究适用性。

原文摘要 · Abstract (English)

Heart Rate Variability (HRV) analysis is a key indicator of cardiac physiological state and aids in disease diagnosis. However, research on HRV parameters in healthy individuals remains limited, and no gold standard exists. This study evaluates HRV indices in 40 healthy adults (20 men, 20 women, aged 30-50) to improve HRV's clinical utility. Using computational methods for signal processing and data analysis, time, frequency, and nonlinear indices were analyzed to address five questions: (1) normality, (2) stability, (3) correlation, (4) reproducibility, and (5) consistency. Key findings: (1) Time-domain and nonlinear indices, particularly global and LF (low frequency), follow normal distributions, with gender differences noted. (2) Most indices are stable except HF (high frequency)-related ones. (3) High correlations in HF-related indices suggest redundancy, indicating only one is necessary in studies. (4) Comparisons with the Fantasia database revealed less than 10% error for most indices, except SD2 and SDNN in women (greater than 15%). (5) Time-domain and nonlinear indices show low inter-study variability, while frequency-domain indices exhibit high variability, limiting cross-study comparisons. The selected indices-ApEn and IRRR (global variability), HRVi and SD2 (LF), and MADRR or rMSSD (HF)-are best suited for accurately representing HRV components and enhancing its clinical and research relevance.

心率变异性健康人群生物信号分析临床应用

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