The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
Physiological time-series analysis: what does regularity quantify?
Abstract
Approximate entropy (ApEn) is a recently developed statistic quantifying regularity and complexity that appears to have potential application to a wide variety of physiological and clinical time-series data. The focus here is to provide a better understanding of ApEn to facilitate its proper utilization, application, and interpretation. After giving the formal mathematical description of ApEn, we provide a multistep description of the algorithm as applied to two contrasting clinical heart rate data sets. We discuss algorithm implementation and interpretation and introduce a general mathematical hypothesis of the dynamics of a wide class of diseases, indicating the utility of ApEn to test this hypothesis. We indicate the relationship of ApEn to variability measures, the Fourier spectrum, and algorithms motivated by study of chaotic dynamics. We discuss further mathematical properties of ApEn, including the choice of input parameters, statistical issues, and modeling considerations, and we conclude with a section on caveats to ensure correct ApEn utilization.
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Cites
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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
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Cited by
Physiological time-series analysis using approximate entropy and sample entropy
Richman, J. S., & Moorman, J. R. (2000) · American Journal of Physiology-Heart and Circulatory Physiology · doi:10.1152/ajpheart.2000.278.6.h2039 · Cited by 7,880
Heart rate variability: A review
Rajendra Acharya, U., Paul Joseph, K., Kannathal, N., Lim, C. M., & Suri, J. S. (2006) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-006-0119-0 · Cited by 2,820
Heart Rate Variability ? A Historical Perspective
Billman, G. E. (2011) · Frontiers in Physiology · doi:10.3389/fphys.2011.00086 · Cited by 786
“There are several other non-linear methods that have been used to evaluate HRV (Denton et al., 1990; Goldberger, 1990; Skinner et al., 1993; Pincus and Goldberger, 1994; Iyengar et al., 1996; Ho et al., 1997; Voss et al., 1998; Mäkikallio et al., 2001a,b; Perkiömäki et al., 2001a,b,c; Jokinen et…”
MethodSassi, 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
Dynamics of stability: the physiologic basis of functional health and frailty
Lipsitz, L. A. (2002) · The Journals of Gerontology Series A: Biological Sciences and Medical Sciences · doi:10.1093/gerona/57.3.b115 · Cited by 646
Metadata
- Authors
- Pincus, S. M., & Goldberger, A. L.
- Venue
- American Journal of Physiology-Heart and Circulatory Physiology
- Publisher
- American Physiological Society
- Published
- 1994-04-01
- Volume
- 266
- Issue
- 4
- Pages
- H1643-H1656
- ISSN
- 0363-6135 (ISSN-L)
- 1522-1539
- OpenAlex
- W1776514298
- Cited by
- 1,315
- References
- 35
- FWCI
- 7.19
- Type
- journal article
- Language
- en
- Open access
- closed
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