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Entropy 2014, 16(7), 4032-4043; doi:10.3390/e16074032
Article

Application of a Modified Entropy Computational Method in Assessing the Complexity of Pulse Wave Velocity Signals in Healthy and Diabetic Subjects

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Received: 19 May 2014; in revised form: 2 July 2014 / Accepted: 8 July 2014 / Published: 17 July 2014
(This article belongs to the Special Issue Entropy and Cardiac Physics)
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Abstract: Using 1000 successive points of a pulse wave velocity (PWV) series, we previously distinguished healthy from diabetic subjects with multi-scale entropy (MSE) using a scale factor of 10. One major limitation is the long time for data acquisition (i.e., 20 min). This study aimed at validating the sensitivity of a novel method, short time MSE (sMSE) that utilized a substantially smaller sample size (i.e., 600 consecutive points), in differentiating the complexity of PWV signals both in simulation and in human subjects that were divided into four groups: healthy young (Group 1; n = 24) and middle-aged (Group 2; n = 30) subjects without known cardiovascular disease and middle-aged individuals with well-controlled (Group 3; n = 18) and poorly-controlled (Group 4; n = 22) diabetes mellitus type 2. The results demonstrated that although conventional MSE could differentiate the subjects using 1000 consecutive PWV series points, sensitivity was lost using only 600 points. Simulation study revealed consistent results. By contrast, the novel sMSE method produced significant differences in entropy in both simulation and testing subjects. In conclusion, this study demonstrated that using a novel sMSE approach for PWV analysis, the time for data acquisition can be substantially reduced to that required for 600 cardiac cycles (~10 min) with remarkable preservation of sensitivity in differentiating among healthy, aged, and diabetic populations.
Keywords: multi-scale entropy; scale factor; pulse wave velocity; age; diabetes multi-scale entropy; scale factor; pulse wave velocity; age; diabetes
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Chang, Y.-C.; Wu, H.-T.; Chen, H.-R.; Liu, A.-B.; Yeh, J.-J.; Lo, M.-T.; Tsao, J.-H.; Tang, C.-J.; Tsai, I.-T.; Sun, C.-K. Application of a Modified Entropy Computational Method in Assessing the Complexity of Pulse Wave Velocity Signals in Healthy and Diabetic Subjects. Entropy 2014, 16, 4032-4043.

AMA Style

Chang Y-C, Wu H-T, Chen H-R, Liu A-B, Yeh J-J, Lo M-T, Tsao J-H, Tang C-J, Tsai I-T, Sun C-K. Application of a Modified Entropy Computational Method in Assessing the Complexity of Pulse Wave Velocity Signals in Healthy and Diabetic Subjects. Entropy. 2014; 16(7):4032-4043.

Chicago/Turabian Style

Chang, Yi-Chung; Wu, Hsien-Tsai; Chen, Hong-Ruei; Liu, An-Bang; Yeh, Jung-Jen; Lo, Men-Tzung; Tsao, Jen-Ho; Tang, Chieh-Ju; Tsai, I-Ting; Sun, Cheuk-Kwan. 2014. "Application of a Modified Entropy Computational Method in Assessing the Complexity of Pulse Wave Velocity Signals in Healthy and Diabetic Subjects." Entropy 16, no. 7: 4032-4043.


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