Key result
Improved least-squares cross-relation method reduces central aortic blood pressure estimation error by ~20%.
Why the study?
Clinical measurement of central aortic blood pressure is intrusive and burdensome, motivating improved mathematical methods to reconstruct central waveforms non-invasively from peripheral pressure signals.
Does an improved cross-relation method with box constraints and mean-matching reduce the error of central aortic blood pressure estimation from peripheral signals?
Does an improved cross-relation method with box constraints and mean-matching reduce the error of central aortic blood pressure estimation from peripheral signals?
An improved mathematical model using box constraints and mean-matching reduces the error in non-invasive central aortic blood pressure estimation by 20%.
May improve non-invasive central aortic BP estimation accuracy; leaves open clinical utility pending validation.
Central aortic blood pressure (CABP) is a very-well recognized source of information to asses the cardiovascular system conditions. However, the clinical measurement protocol of this pulse wave is very intrusive and burdensome as it requires expert staff and complicated invasive settings. On the other hand, the measurement of peripheral blood pressure is much more straightforward and easy-to-get non-invasively. Several mathematical tools have been employed in the past few decades to reconstruct CABP waveforms from distorted peripheral pressure signals. More specifically, the cross-relation approach together with the widely used least-squares method, are shown to be effective as a way to estimate CABP waves. In this paper, we propose an improved cross-relation method that leverages the values of the diastolic and systolic pressures as box constraints. In addition, a mean-matching criterion is introduced to relax the need for the input and output mean values to be strictly equal. Using the proposed method, the root mean squared error is reduced by approximately 20% while the computational complexity is not significantly increased.
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Magbool et al. (2020) studied Central aortic blood pressure estimation. Improved cross-relation method with mean matching and box constraints vs. Standard cross-relation approach was evaluated on Root mean squared error (RMSE). An improved cross-relation method using least-squares with mean matching and box constraints reduced the root mean squared error of central aortic blood pressure estimation by approximately 20%.
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