By Topic

Approximate entropy for all signals

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Ki H. Chon ; SUNY Stony Brook, Stony Brook, New York, USA ; Christopher G. Scully ; Sheng Lu

In this study, computer simulation examples consisting of various signals with different complexity were compared. It was found that neither approximate entropy (ApEn) nor sample entropy (SampEn) methods was accurate in measuring signals' complexity when the recommended values (e.g., m = 2 and r = 0.1-0.2 times the standard deviation of the signal) were strictly adhered to. However, when we selected the maximum ApEn value as determined by considering many different r values, we were able to correctly discern a signal's complexity for both synthetic and experimental data. However, this requires that many different choices of r values need to be considered. This is a very cumbersome and time-consuming process. Thus, the primary goal of the present work is to illustrate our recently developed method that can automatically select the appropriate tolerance threshold value r, which corresponds to the maximum ApEn value, without resorting to the calculation of ApEn for each of the threshold values selected in the range of zero and one times the standard deviation.

Published in:

IEEE Engineering in Medicine and Biology Magazine  (Volume:28 ,  Issue: 6 )