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• W2340586723 abstract "Assessment of pulse waves that recorded in the microvascular bed when the heart throwing blood appears to be the essential diagnostic method. The conventional non-invasive methods are mostly based on measurement of pulse wave velocity (PWV) which was proved to be the predictor of cardiovascular system state. Photoplethysmography (PPG) is a simple and low-cost optical technique that can be used to detect blood volume changes in the microvascular bed of tissue. Since many factors contribute to PWV formation, it shows considerable variability and sensitive to the current physiological state. Traditional mathematical methods that examine this variability in the frequency domain, such as Fourier analysis, not always the best choice since the non-stationary features of PWV signal. A relatively new, but already popular tool, Wavelet transform, allows multiresolution analysis in time-frequency domain of non-stationary signals. In our work we apply Wavelet Cross Spectrum (WCS) and Wavelet-Based Coherence (WBC) to reveal the similarities between two PWV time series recorded simultaneously from left and right arms. We find that the degree correlation and the time lag between these signals considerably depend on frequency range. On this basis, we hypothesize the systemic (neurogenic) origin of high-frequency (0.2 Hz) PWV variations." @default.
• W2340586723 created "2016-06-24" @default.
• W2340586723 creator A5023447876 @default.
• W2340586723 creator A5054022124 @default.
• W2340586723 creator A5072944845 @default.
• W2340586723 date "2016-04-21" @default.
• W2340586723 modified "2023-09-23" @default.
• W2340586723 title "Application of cross-wavelet transform to pulse velocity data: seeking for inter-limb coherence" @default.
• W2340586723 cites W2154261306 @default.
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• W2340586723 doi "https://doi.org/10.1117/12.2229851" @default.
• W2340586723 hasPublicationYear "2016" @default.
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