Title :
Cardiovascular Signal Decomposition and Estimation with the Extended Kalman Smoother
Author :
McNames, James ; Aboy, Mateo
Author_Institution :
Dept. of Electr. & Comput. Eng., Portland State Univ., OR
fDate :
Aug. 30 2006-Sept. 3 2006
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
Keywords :
Kalman filters; blood vessels; cardiovascular system; haemodynamics; medical signal processing; oximetry; pneumodynamics; smoothing methods; statistical analysis; arterial blood pressure; cardiovascular signal decomposition; central venous pressure; extended Kalman filter; extended Kalman smoother; heart rate; pulse oximetry; pulse pressure variation; respiratory rate; signal estimation; statistical state-space model; Amplitude modulation; Cardiology; Frequency estimation; Heart rate; Kalman filters; Power harmonic filters; Pulse modulation; Signal processing algorithms; Signal resolution; State estimation;
Conference_Titel :
Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE
Conference_Location :
New York, NY
Print_ISBN :
1-4244-0032-5
Electronic_ISBN :
1557-170X
DOI :
10.1109/IEMBS.2006.260463
