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Background <p>Heart rate variability (HRV) analysis is widely used to assess autonomic nervous function (ANF); however, conventional frequency-domain indices require recording durations that may limit their applicability in settings requiring rapid or repeated measurements. This study investigated whether measurement duration could be reduced by estimating high-frequency power (<i>HF</i>), an index of parasympathetic modulation, from ultra-short-term (UST) recording windows using a Lorenz plot (LP)-based estimation model.</p> Methods <p>Electrocardiographic data were recorded during a 2-min resting, eyes-closed condition. <i>HF</i> was calculated exclusively from the full 120-s recording using frequency-domain analysis and served as the reference outcome. LP indices were computed from progressively shorter R–R interval (RRI) windows (120–5&#xa0;s) and, together with age, were used to construct regression models to estimate the 120-s <i>HF</i> reference value. No frequency-domain analysis was performed on the shortened windows.</p> Results <p>The LP-based estimation model demonstrated robust performance across window lengths. Even when LP indices were computed from as little as 5&#xa0;s of data, the model retained acceptable predictive accuracy for estimating the <i>HF</i> reference value derived from the 120-s recording (adjusted <i>R</i><sup>2</sup> = 0.67).</p> Conclusions <p>Parasympathetic modulation reflected in conventional 120-s frequency-domain <i>HF</i> analysis can be estimated with practical accuracy from UST recordings as short as 5&#xa0;s using the LP-based estimation model. The proposed model does not confer interchangeability with standard frequency-domain <i>HF</i> indices across time scales. Rather, it offers a practical marker for rapid estimation of the 120-s frequency-domain <i>HF</i> reference value when longer recordings are impractical.</p>

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A novel application of the lorenz plot method for ultra-short-term evaluation of autonomic nervous function

  • 期刊论文

  • 发表日期：

    2026年3月17日

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  • Sakura Tatsumi,
  • Daisuke Kuratsune,
  • Hirohiko Kuratsune

摘要

Background

Heart rate variability (HRV) analysis is widely used to assess autonomic nervous function (ANF); however, conventional frequency-domain indices require recording durations that may limit their applicability in settings requiring rapid or repeated measurements. This study investigated whether measurement duration could be reduced by estimating high-frequency power (HF), an index of parasympathetic modulation, from ultra-short-term (UST) recording windows using a Lorenz plot (LP)-based estimation model.

Methods

Electrocardiographic data were recorded during a 2-min resting, eyes-closed condition. HF was calculated exclusively from the full 120-s recording using frequency-domain analysis and served as the reference outcome. LP indices were computed from progressively shorter R–R interval (RRI) windows (120–5 s) and, together with age, were used to construct regression models to estimate the 120-s HF reference value. No frequency-domain analysis was performed on the shortened windows.

Results

The LP-based estimation model demonstrated robust performance across window lengths. Even when LP indices were computed from as little as 5 s of data, the model retained acceptable predictive accuracy for estimating the HF reference value derived from the 120-s recording (adjusted R2 = 0.67).

Conclusions

Parasympathetic modulation reflected in conventional 120-s frequency-domain HF analysis can be estimated with practical accuracy from UST recordings as short as 5 s using the LP-based estimation model. The proposed model does not confer interchangeability with standard frequency-domain HF indices across time scales. Rather, it offers a practical marker for rapid estimation of the 120-s frequency-domain HF reference value when longer recordings are impractical.