The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Sample entropy analysis of neonatal heart rate variability
Abstract
Abnormal heart rate characteristics of reduced variability and transient decelerations are present early in the course of neonatal sepsis. To investigate the dynamics, we calculated sample entropy, a similar but less biased measure than the popular approximate entropy. Both calculate the probability that epochs of window length m that are similar within a tolerance r remain similar at the next point. We studied 89 consecutive admissions to a tertiary care neonatal intensive care unit, among whom there were 21 episodes of sepsis, and we performed numerical simulations. We addressed the fundamental issues of optimal selection of m and r and the impact of missing data. The major findings are that entropy falls before clinical signs of neonatal sepsis and that missing points are well tolerated. The major mechanism, surprisingly, is unrelated to the regularity of the data: entropy estimates inevitably fall in any record with spikes. We propose more informed selection of parameters and reexamination of studies where approximate entropy was interpreted solely as a regularity measure.
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Cites
Heart rate variability: Standards of measurement, physiological interpretation, and clinical use
Malik, M., Bigger, J. T., Camm, A. J., Kleiger, R. E., Malliani, A., Moss, A. J., & Schwartz, P. J. (1996) · European Heart Journal · doi:10.1093/oxfordjournals.eurheartj.a014868 · Cited by 15,289
Approximate entropy as a measure of system complexity.
Pincus, S. M. (1991) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.88.6.2297 · Cited by 5,811
Cited by
The Appropriate Use of Approximate Entropy and Sample Entropy with Short Data Sets
Yentes, J. M., Hunt, N., Schmid, K. K., Kaipust, J. P., McGrath, D., & Stergiou, N. (2013) · Annals of Biomedical Engineering · doi:10.1007/s10439-012-0668-3 · Cited by 893
Sassi, R., Cerutti, S., Lombardi, F., Malik, M., Huikuri, H. V., Peng, C.-K., Schmidt, G., Yamamoto, Y., Reviewers:, D., Gorenek, B., et al. (2015) · Europace · doi:10.1093/europace/euv015 · Cited by 727
Emotion recognition using wireless signals
Zhao, M., Adib, F., & Katabi, D. (2016) · Proceedings of the 22nd Annual International Conference on Mobile Computing and Networking · doi:10.1145/2973750.2973762 · Cited by 461
Dynamical structure of center-of-pressure trajectories in patients recovering from stroke
Roerdink, M., De Haart, M., Daffertshofer, A., Donker, S. F., Geurts, A. C. H., & Beek, P. J. (2006) · Experimental Brain Research · doi:10.1007/s00221-006-0441-7 · Cited by 302
Atypical EEG complexity in autism spectrum conditions: A multiscale entropy analysis
Catarino, A., Churches, O., Baron-Cohen, S., Andrade, A., & Ring, H. (2011) · Clinical Neurophysiology · doi:10.1016/j.clinph.2011.05.004 · Cited by 271
Metadata
- Authors
- Lake, D. E., Richman, J. S., Griffin, M. P., & Moorman, J. R.
- Venue
- American Journal of Physiology-Regulatory, Integrative and Comparative Physiology
- Publisher
- American Physiological Society
- Published
- 2002-09-01
- Volume
- 283
- Issue
- 3
- Pages
- R789-R797
- ISSN
- 0363-6119 (ISSN-L)
- 1522-1490
- OpenAlex
- W2118183148
- Cited by
- 1,233
- References
- 2
- FWCI
- 6.02
- Type
- journal article
- Language
- en
- Open access
- closed
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- Lake, D. E., Richman, J. S., Griffin, M. P., & Moorman, J. R. (2002). Sample entropy analysis of neonatal heart rate variability. American Journal of Physiology-Regulatory, Integrative and Comparative Physiology. https://doi.org/10.1152/ajpregu.00069.2002
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