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Separation of Forward-Backward Waves in the Arterial System using Multi-Gaussian Approach from Single Pulse Waveform
Date Issued
01-01-2021
Author(s)
Manoj, Rahul
Raj Kiran, V.
Nabeel, P. M.
Indian Institute of Technology, Madras
Indian Institute of Technology, Madras
Abstract
The arterial pulse waveform has an immense wealth of information in its morphology yet to be explored and translated to clinical practice. Wave separation analysis involves decomposing a pulse wave (pressure or diameter waveform) into a forward wave and a backward wave. The backward wave accumulates reflections due to arterial stiffness gradient, branching and geometric tapering of blood vessels across the arterial tree. The state-of-the-art wave separation analysis is based on estimating the input impedance of the target artery in the frequency/time domain, which requires simultaneously measured or modelled flow velocity and pressure waveform. We are proposing a new method of wave separation analysis using a multi-gaussian decomposition. The novelty of this approach is that it requires only a single pulse waveform at the target artery. Our method was compared against the triangular waveform-based impedance method. We successfully separated forward and backward waveform from the pressure waveform with maximum RMSE less than 5 mmHg and mean RMSE of 1.31 mmHg when compared against the triangular flow/impedance method. Results demonstrated a statistically significant correlation (r>0.66, p<0.0001) for Reflection Magnitude (RM) and Reflection Index (RI) for the multi-gaussian approach against the triangular flow method for 105 virtual subjects. The range of RM was from 0.35 to 0.97 (RI: 27.53% to 49.29%). This method proves to be a technique for evaluating reflection parameters if only a single pulse measurement is available from any artery.Clinical Relevance - This simulation study supplements the evidence for wave reflections. It provides a new method to study wave reflections using only a single pulse waveform without the need for any measured or modelled flow.