Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Quantification of evolution from order to randomness in practical time series analysis

S M Pincus

    Methods in Enzymology
    |January 1, 1994
    PubMed
    Summary

    This study introduces Approximate Entropy (ApEn), a new statistic for analyzing time series data, offering a robust measure of process regularity and complexity applicable to biological systems.

    Related Concept Videos

    You might also read

    Related Articles

    Articles linked to this work by shared authors, journal, and citation graph.

    Sort by
    Same author

    Heparin toxicity following allogeneic bone marrow infusion.

    Bone marrow transplantation·2007
    Same author

    Noninvasive in vivo investigative probes of adaptive mechanisms of neuroendocrine regulation: the paradigm of the hypothalamo-pituitary-gonadal axis in the aging male.

    Journal of endocrinological investigation·2003
    Same author

    Sexual dimorphism in the synchrony of joint growth hormone and cortisol dynamics in children with classic 21-hydroxylase deficiency.

    Journal of pediatric endocrinology & metabolism : JPEM·2003
    Same author

    Assessing serial irregularity and its implications for health.

    Annals of the New York Academy of Sciences·2002
    Same author

    Impact of pulsatility on the ensemble orderliness (approximate entropy) of neurohormone secretion.

    American journal of physiology. Regulatory, integrative and comparative physiology·2001
    Same author

    Disruption of the synchronous secretion of leptin, LH, and ovarian androgens in nonobese adolescents with the polycystic ovarian syndrome.

    The Journal of clinical endocrinology and metabolism·2001

    Area of Science:

    • Biomedical Engineering
    • Time Series Analysis
    • Complexity Science

    Background:

    • Traditional methods for time series analysis often struggle with complex biological data.
    • Existing algorithms like correlation dimension are limited to specific types of deterministic systems.
    • There is a need for a versatile statistic to quantify regularity and complexity in diverse data.

    Purpose of the Study:

    • To describe Approximate Entropy (ApEn), a novel and practical statistic for time series analysis.
    • To highlight ApEn's utility in quantifying the continuum from order to randomness.
    • To demonstrate ApEn's applicability to biological systems and its complementary nature to existing methods.

    Main Methods:

    • Introduction of Approximate Entropy (ApEn) as a measure of time series regularity.
    • Discussion of ApEn's properties: noise and outlier robustness, applicability to medium-sized datasets (N>=100).
    • Explanation of parameter selection (m: window length, r: tolerance width) and normalized ApEn for SD decorrelation.

    Main Results:

    • ApEn is robust to noise below a filter level and outliers.
    • ApEn is finite for stochastic, deterministic, and composite processes, reflecting increasing complexity.
    • Normalized ApEn allows separation of standard deviation changes from regularity changes.

    Conclusions:

    • ApEn offers a valuable, practical tool for analyzing time series data, especially in biological contexts.
    • Its ability to handle complex, noisy, and mixed processes distinguishes it from 'chaos' algorithms.
    • ApEn should be used alongside other statistical methods for comprehensive data analysis.

    Related Experiment Videos