Blind Estimation of Central Blood Pressure Using Least-Squares with Mean Matching and Box Constraints
Al-Naffouri, Tareq Y.
KAUST DepartmentComputational Bioscience Research Center (CBRC)
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Electrical Engineering Program
Estimation, Modeling and ANalysis Group
Online Publication Date2020-08-28
Print Publication Date2020-07
Permanent link to this recordhttp://hdl.handle.net/10754/665145
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AbstractCentral 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.
CitationMagbool, A., Bahloul, M. A., Ballal, T., Al-Naffouri, T. Y., & Laleg-Kirati, T.-M. (2020). Blind Estimation of Central Blood Pressure Using Least-Squares with Mean Matching and Box Constraints. 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). doi:10.1109/embc44109.2020.9176258
Conference/Event name2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)