Application of Continuous Wavelet Transformation to monitor diabetic neuropathy and vasomotion reaction patterns

Photoplethysmographic (PPG) signals reflect the regulations of heart rate, blood and stroke volume and peripheral resistance of blood vessels. The technique of Continuous Wavelet Transformation (CWT) is applied to the irregular and weak PPG signals. The CWT of the PPG data is found to be a specific, sensitive, nonlinear method for the in vivo identification of hearth circulation patterns. The disadvantage of the traditionally used STFT is that this technique averages short-duration components and cannot capture those components that last longer than the window itself. This problem was solved by using the CWT. With our approach a monitoring of diabetic microangiopathy status, compensation the blood pressure drop during dialysis sessions by vascular vasoconstriction and the linkage between abnormal hemodynamic parameters and PPG-pulse features where observed and should be further quantified in order to deliver parametric diagnostic data for the medical personal.