title: Cardiovascular signal decomposition and estimation with the extended Kalman smoother.
abstract: Cardiovascular signals such as arterial blood pressure (ABP), pulse oximetry (SpO2) and central venous pressure (CVP) contain useful information such as heart rate, respiratory rate, and pulse pressure variation (PPV). We present a statistical state-space model of cardiovascular signals that can be used with the extended Kalman filter or smoother to simultaneously estimate and track many cardiovascular parameters of interest. We demonstrate the algorithm's tracking capabilities with a real ABP signal.
authors.affiliation: Dept. of Electr. & Comput. Eng., Portland State Univ., OR, USA. mcnames@pdx.edu
authors.forename: J
authors.initials: J
authors.lastname: McNames
authors.forename: M
authors.initials: M
authors.lastname: Aboy
mesh_terms: D000465:Algorithms; D016477:Artifacts; D001794:Blood Pressure; D002320:Cardiovascular Physiological Phenomena; D006339:Heart Rate; D006801:Humans; D008955:Models, Cardiovascular; D010092:Oximetry; D015398:Signal Transduction