Effects of ecg data length on heart rate variability among young healthy adults

En Fan Chou, Michelle Khine, Thurmon Lockhart, Rahul Soangra

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

The relationship between the robustness of HRV derived by linear and nonlinear methods to the required minimum data lengths has yet to be well understood. The normal electrocardiog-raphy (ECG) data of 14 healthy volunteers were applied to 34 HRV measures using various data lengths, and compared with the most prolonged (2000 R peaks or 750 s) by using the Mann–Whitney U test, to determine the 0.05 level of significance. We found that SDNN, RMSSD, pNN50, normal-ized LF, the ratio of LF and HF, and SD1 of the Poincaré plot could be adequately computed by small data size (60–100 R peaks). In addition, parameters of RQA did not show any significant dif-ferences among 60 and 750 s. However, longer data length (1000 R peaks) is recommended to cal-culate most other measures. The DFA and Lyapunov exponent might require an even longer data length to show robust results. Conclusions: Our work suggests the optimal minimum data sizes for different HRV measures which can potentially improve the efficiency and save the time and effort for both patients and medical care providers.

Original languageEnglish (US)
Article number6286
JournalSensors
Volume21
Issue number18
DOIs
StatePublished - Sep 2021

Keywords

  • Autonomic nervous system
  • Chaos
  • Electrocardiography ECG
  • Fluctuations
  • Heart rate variabil-ity
  • Nonlinear analysis

ASJC Scopus subject areas

  • Analytical Chemistry
  • Information Systems
  • Atomic and Molecular Physics, and Optics
  • Biochemistry
  • Instrumentation
  • Electrical and Electronic Engineering

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