title: Oscillometric Blood Pressure Estimation: Past, Present, and Future.
abstract: The use of automated blood pressure (BP) monitoring is growing as it does not require much expertise and can be performed by patients several times a day at home. Oscillometry is one of the most common measurement methods used in automated BP monitors. A review of the literature shows that a large variety of oscillometric algorithms have been developed for accurate estimation of BP but these algorithms are scattered in many different publications or patents. Moreover, considering that oscillometric devices dominate the home BP monitoring market, little effort has been made to survey the underlying algorithms that are used to estimate BP. In this review, a comprehensive survey of the existing oscillometric BP estimation algorithms is presented. The survey covers a broad spectrum of algorithms including the conventional maximum amplitude and derivative oscillometry as well as the recently proposed learning algorithms, model-based algorithms, and algorithms that are based on analysis of pulse morphology and pulse transit time. The aim is to classify the diverse underlying algorithms, describe each algorithm briefly, and discuss their advantages and disadvantages. This paper will also review the artifact removal techniques in oscillometry and the current standards for the automated BP monitors.
authors.forename: Mohamad
authors.initials: M
authors.lastname: Forouzanfar
authors.forename: Hilmi R
authors.initials: HR
authors.lastname: Dajani
authors.forename: Voicu Z
authors.initials: VZ
authors.lastname: Groza
authors.forename: Miodrag
authors.initials: M
authors.lastname: Bolic
authors.forename: Sreeraman
authors.initials: S
authors.lastname: Rajan
authors.forename: Izmail
authors.initials: I
authors.lastname: Batkin
mesh_terms: D000465:Algorithms; D001794:Blood Pressure / Q000502:physiology; D001795:Blood Pressure Determination; D006801:Humans; D016571:Neural Networks, Computer; D009991:Oscillometry