Pincus, S. () Approximate Entropy (ApEn) as a Complexity Measure. Chaos, 5, APPROXIMATE ENTROPY: A COMPLEXITY MEASURE FOR. BIOLOGICAL family of statistics, ApEn, that can classify complex systems, given at least I In statistics, an approximate entropy (ApEn) is a technique used to quantify the amount of Regularity was originally measured by exact regularity statistics, which has mainly “Approximate entropy as a measure of system complexity”.

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Approximate entropy (ApEn) as a complexity measure. – Semantic Scholar

The American Journal of Physiology. Views Read Edit View history. For an excellent review of the shortcomings of and the strengths of alternative statistics, see reference [5]. Finally, we calculate that. Artificial Intelligence in Medicine. The correlation is demonstrated using two healthy subjects compared against a control group.

This is a very small value of ApEn, which suggests that the original time series is highly predictable as indeed it is. Heart and Circulatory Physiology. PuthankattilPaul K.

If you have any comments, feedback, or particular questions regarding this page, please send them to the webmaster. MurrayRoger T. Journal of Clinical Monitoring and Computing. In statisticsan approximate entropy ApEn is a technique used to quantify the amount of regularity and the unpredictability of fluctuations over time-series data. A notion of behavioural entropy and hysteresis is introduced as two different forms of compound measures.


Doing so, we obtain: The application of the compound measures is shown to correlate with complexity analysis. Given a sequenceconsisting of instantaneous heart rate measurements, we must choose values for two input parameters, andto compute the approximate entropy,of the sequence. If the time series is highly irregular, the occurrence of similar patterns will not be predictive for the following measurements, and will be relatively large.

Here, we provide a brief summary of the calculations, as applied to a time series of heart rate measurements. This description is provided com;lexity so that researchers who wish to use ApEn can write their own code for doing so. Applied MathematicsVol.

AhearnAlison D. SokunbiGeorge G. Regularity was originally measured by exact regularity statistics, which has mainly centered on various entropy measures. Two patterns, andare similar if the difference between any pair of corresponding measurements in the patterns is less thani. The first question to be answered is: American Journal of Physiology. An example may help to clarify the process of calculating.


Applications of a constitutive framework providing compound complexity analysis and indexing of coarse-grained self-similar time series representing behavioural data are presented. The ApEn algorithm counts each sequence as matching itself to avoid the occurrence of ln 0 in the calculations. In order to obtainwe need to repeat all of the calculations above for. Entropy, Complexity and Stability.

Approximate Entropy (ApEn)

Moment statisticssuch as mean and variancewill not distinguish between these two series. Approximate entropy as a measure of system complexity. By the same reasoning, is similar to,The quantity is the fraction of patterns of length that resemble the pattern of the same length that begins at interval.

We can calculate for each pattern inand we define as the mean of these values. Since we have chosen as the similarity criterion, this means that each of the 5 components of must be within units of the corresponding component of.

Tapia CortezJames W.