title: Bayesian fusion algorithm for improved oscillometric blood pressure estimation.
abstract: A variety of oscillometric algorithms have been recently proposed in the literature for estimation of blood pressure (BP). However, these algorithms possess specific strengths and weaknesses that should be taken into account before selecting the most appropriate one. In this paper, we propose a fusion method to exploit the advantages of the oscillometric algorithms and circumvent their limitations. The proposed fusion method is based on the computation of the weighted arithmetic mean of the oscillometric algorithms estimates, and the weights are obtained using a Bayesian approach by minimizing the mean square error. The proposed approach is used to fuse four different oscillometric blood pressure estimation algorithms. The performance of the proposed method is evaluated on a pilot dataset of 150 oscillometric recordings from 10 subjects. It is found that the mean error and standard deviation of error are reduced relative to the individual estimation algorithms by up to 7 mmHg and 3 mmHg in estimation of systolic pressure, respectively, and by up to 2 mmHg and 3 mmHg in estimation of diastolic pressure, respectively.
authors.affiliation: School of Electrical Engineering and Computer Science, University of Ottawa, 800 King Edward Avenue, Ottawa, ON K1N 6N5, Canada; Department of Electrical Engineering, Stanford University, 350 Serra Mall, Stanford, CA 94305, USA. Electronic address: mforo040@uottawa.ca.
authors.forename: Mohamad
authors.initials: M
authors.lastname: Forouzanfar
authors.affiliation: School of Electrical Engineering and Computer Science, University of Ottawa, 800 King Edward Avenue, Ottawa, ON K1N 6N5, Canada.
authors.forename: Hilmi R
authors.initials: HR
authors.lastname: Dajani
authors.affiliation: School of Electrical Engineering and Computer Science, University of Ottawa, 800 King Edward Avenue, Ottawa, ON K1N 6N5, Canada.
authors.forename: Voicu Z
authors.initials: VZ
authors.lastname: Groza
authors.affiliation: School of Electrical Engineering and Computer Science, University of Ottawa, 800 King Edward Avenue, Ottawa, ON K1N 6N5, Canada.
authors.forename: Miodrag
authors.initials: M
authors.lastname: Bolic
authors.affiliation: Department of Systems and Computer Engineering, Carleton University, Ottawa, ON K1S 5B6, Canada.
authors.forename: Sreeraman
authors.initials: S
authors.lastname: Rajan
authors.affiliation: School of Electrical Engineering and Computer Science, University of Ottawa, 800 King Edward Avenue, Ottawa, ON K1N 6N5, Canada.
authors.forename: Izmail
authors.initials: I
authors.lastname: Batkin
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D001795:Blood Pressure Determination / Q000379:methods*; D009991:Oscillometry
keywords: Bayesian estimator; Blood pressure estimation; Fusion; Oscillometry