Effects of ECG Data Length on Heart Rate Variability Among Young Healthy Adults

Authors

En-Fan Chou, University of California, IrvineFollow
Michelle Khine, University of California, IrvineFollow
Thurmon Lockhart, Arizona State UniversityFollow
Rahul Soangra, Chapman UniversityFollow

Document Type

Article

Publication Date

9-19-2021

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 electrocardiography (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, normalized 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 differences among 60 and 750 s. However, longer data length (1000 R peaks) is recommended to calculate 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.

Comments

This article was originally published in Sensors, volume 21, issue 18, in 2021. https://doi.org/10.3390/s21186286

Recommended Citation

Chou EF, Khine M, Lockhart T, Soangra R. Effects of ECG Data Length on Heart Rate Variability among Young Healthy Adults. Sensors (Basel). 2021;21(18):6286. https://doi.org/10.3390/s21186286

Peer Reviewed

1

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This work is licensed under a Creative Commons Attribution 4.0 License.