Abstract
The harmonic analysis (HA) of arterial radial pulses in humans has been widely investigated in recent years for clinical applications of traditional Chinese medicine. This study aimed at establishing the validity of carrying out HA on synchronous peripheral volume pulses for predicting diabetes-induced subtle changes in heart energy. In this study, 141 subjects (Group 1: 63 healthy elderly subjects; Group 2: 78 diabetic subjects) were enrolled at the same hospital. After routine blood sampling, all synchronous electrocardiogram (ECG) and photoplethysmography (PPG) measurements (i.e., at the six locations) were acquired in the morning. HA of synchronous peripheral volume pulses and radial pulse waves was performed and analyzed after a short period of an ensemble averaging process based on the R-wave peak location. This study utilized HA for the peripheral volume pulses and found that the averaged total pulse energy (i.e., the C0 of the DTFS) was identical in the same subject. A logistic regression model with C0 and a waist circumference variable showed a graded association with the risk of developing type 2 diabetes. The adjusted odds ratio for C0 and the waist circumference were 0.986 (95% confidence interval: 0.977, 0.994) and 1.130 (95% confidence interval: 1.045, 1.222), respectively. C0 also showed significant negative correlations with risk factors for type 2 diabetes mellitus, including glycosylated hemoglobin and fasting plasma glucose (r = −0.438, p < 0.001; r = −0.358, p < 0.001, respectively). This study established a new application of harmonic analysis in synchronous peripheral volume pulses for clinical applications. The findings showed that the C0 could be used as a prognostic indicator of a protective factor for predicting type 2 diabetes.
Highlights
Introduction iationsThere are several data decomposition methods in pulse wave analysis, of which harmonic analysis (HA) for discrete-time Fourier series (DTFS) [1,2,3], wavelet transformation [4], and ensemble empirical mode decomposition [5], among others, are efficient ways of viewing waveforms with regard to time/frequency or a nonlinear domain
Without using the information of the blood samples, we focused on the parameters that were obtained at home for the prediction of risk factors of type 2 diabetes
Six synchronous peripheral volume pulse signals were obtained from a six-channel ECG-Pulse Wave Velocity (PWV) system, and the synchronous peripheral volume pulse signals were decomposed with DTFS and analyzed, with the first eleven coefficients of the harmonic terms of the synchronous peripheral volume pulse signals (i.e., C0 –C10 in DTFS)
Summary
There are several data decomposition methods in pulse wave analysis, of which harmonic analysis (HA) for discrete-time Fourier series (DTFS) [1,2,3], wavelet transformation [4], and ensemble empirical mode decomposition [5], among others, are efficient ways of viewing waveforms with regard to time/frequency or a nonlinear domain. The HA of arterial pressure pulses has standard protocols and reliability assessments, as well as being established in [6,7], for effective harmonic wave analyzers Professors Tsai et al indicated that the harmonic characteristics of the radial artery in the wrist at different positions and different parameters were not identical, and recommended that any measurement location in future studies on the HA of pressure.
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