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Decreased heart rate variability (HRV), indicative of autonomic nervous system (ANS) dysfunction, is commonly observed in patients with type 2 diabetes mellitus (T2DM), affecting both sympathetic and parasympathetic modulation. A free version of a commercial software has become an important tool for HRV analysis, providing a comprehensive evaluation of parameters. However, its lack of an automatic algorithm for selecting a 5-min time-window for short-term evaluations makes the analysis time-consuming, operator-dependent, and susceptible to bias. This study aims to compare the impact of manual versus a novel automatic time-window selection algorithm for HRV analysis in T2DM individuals employing the open-source PyHRV library. Thirty-one individuals with T2DM were included in the analyses. No statistically significant differences were observed between manual and automatic time- window selection in this population (p > 0.05), suggesting that the automatic selection algorithm can be employed without compromising the HRV results.

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Analysis of Heart Rate Variability in Type II Diabetics: Comparison of Manual and a Novel Automatic Assessment

  • 会议论文

  • 发表日期：

    2025年

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  • Aldair Darlan Santos-de-Araújo,
  • Daniela Bassi-Dibai,
  • Marinete Rodrigues de Farias Diniz,
  • Abraão Albino Mendes Junior,
  • Audrey Borghi-Silva,
  • Henrique Takachi Moriya,
  • Felipe Fava de Lima

摘要

Decreased heart rate variability (HRV), indicative of autonomic nervous system (ANS) dysfunction, is commonly observed in patients with type 2 diabetes mellitus (T2DM), affecting both sympathetic and parasympathetic modulation. A free version of a commercial software has become an important tool for HRV analysis, providing a comprehensive evaluation of parameters. However, its lack of an automatic algorithm for selecting a 5-min time-window for short-term evaluations makes the analysis time-consuming, operator-dependent, and susceptible to bias. This study aims to compare the impact of manual versus a novel automatic time-window selection algorithm for HRV analysis in T2DM individuals employing the open-source PyHRV library. Thirty-one individuals with T2DM were included in the analyses. No statistically significant differences were observed between manual and automatic time- window selection in this population (p > 0.05), suggesting that the automatic selection algorithm can be employed without compromising the HRV results.