Using Complexity and Spectral Analyses of Noninvasive LDF Signals in Patients with Metabolic Syndrome

Hsin Hsiu, Hsiao-Feng Hu and Yaw-Wen Chang

Complexity, 2018, vol. 2018, 1-6

Abstract:

This study performed skin-surface measurements with the aim of verifying if complexity and spectral analyses applied to laser-Doppler-flowmetry (LDF) signals can be used to discriminate control subjects and patients with metabolic syndrome (MetS) and patients with premetabolic syndrome (pre-MetS). The study participants ( ) were assigned to three age-matched groups based on the application of MetS criteria. Beat-to-beat analysis was performed to obtain the mean blood flow (DC), and then approximate entropy (ApEn) values for the 10-minute DC sequences (DC_ApEn) were calculated to evaluate the signal complexity. The wavelet transform was applied and yielded periodic oscillations with five characteristic frequency peaks (defined as FR1–FR5) whose relative energy contributions (RECs) were calculated. DC_ApEn was significantly smaller in MetS and pre-MetS (with one or two Mets factors) patients than in controls, whereas there were no significant differences in DC. The REC of FR1 was significantly smaller while the REC of FR4 was significantly larger in pre-MetS than in MetS. These results indicate the presence of significant differences in ApEn and spectral indexes, which may be partly attributable to changes in microcirculatory regulatory activities accompanying the progression of MetS. The present findings may be pertinent to the early detection of the microcirculatory impairments associated with MetS.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:6898024

DOI: 10.1155/2018/6898024

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