Measuring Coupling of Rhythmical Time Series Using Cross Sample Entropy and Cross Recurrence Quantification Analysis.

John McCamley, William Denton, Elizabeth Lyden, Jennifer M Yentes
Author Information
  1. John McCamley: MORE Foundation, 18444 N. 25th Ave, Suite 110, Phoenix, AZ 85023, USA.
  2. William Denton: Center for Research in Human Movement Variability, University of Nebraska Omaha, 6160 University Drive, Omaha, NE 68182-0860, USA.
  3. Elizabeth Lyden: College of Public Health, University of Nebraska Medical Center, 984355 Medical Center, Omaha, NE 68198-4355, USA.
  4. Jennifer M Yentes: Center for Research in Human Movement Variability, University of Nebraska Omaha, 6160 University Drive, Omaha, NE 68182-0860, USA. ORCID

Abstract

The aim of this investigation was to compare and contrast the use of cross sample entropy (xSE) and cross recurrence quantification analysis (cRQA) measures for the assessment of coupling of rhythmical patterns. Measures were assessed using simulated signals with regular, chaotic, and random fluctuations in frequency, amplitude, and a combination of both. Biological data were studied as models of normal and abnormal locomotor-respiratory coupling. Nine signal types were generated for seven frequency ratios. Fifteen patients with COPD (abnormal coupling) and twenty-one healthy controls (normal coupling) walked on a treadmill at three speeds while breathing and walking were recorded. xSE and the cRQA measures of percent determinism, maximum line, mean line, and entropy were quantified for both the simulated and experimental data. In the simulated data, xSE, percent determinism, and entropy were influenced by the frequency manipulation. The 1 : 1 frequency ratio was different than other frequency ratios for almost all measures and/or manipulations. The patients with COPD used a 2 : 3 ratio more often and xSE, percent determinism, maximum line, mean line, and cRQA entropy were able to discriminate between the groups. Analysis of the effects of walking speed indicated that all measures were able to discriminate between speeds.

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Grants

  1. L30 HL129255/NHLBI NIH HHS
  2. P20 GM109090/NIGMS NIH HHS

MeSH Term

Aged
Case-Control Studies
Entropy
Exercise Test
Female
Humans
Male
Middle Aged
Models, Statistical
Nonlinear Dynamics
Oscillometry
Pulmonary Disease, Chronic Obstructive
Respiration
Signal Processing, Computer-Assisted
Walking

Word Cloud

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