Arterial Blood Pressure Signal Tracking

Filtering of Arterial Blood Pressure Signal Artifact using the Extended Kalman Filter

Arterial blood pressure signal (from MIMIC II Database) with measurements and tracking signal overlaid.

The figure above depicts several seconds of raw arterial blood pressure (ABP) data obtained from a patient within the MIMIC II physiologic waveform database. [1,2]

This figure shows a raw signal with a tracking signal based on the extended Kalman filter (EKF) overlaid. In this case, the signal error and the process noise are very small (signal noise 0.1 mmHg, process noise 0.5 mmHg). With these settings, the filter tracks the actual signal very closely, and makes it appear as if there is not difference between signal measurement and track.

The full analysis is available at the following link in PDF form:

ABP Tracking via EKF

[1] M. Saeed, M. Villarroel, A.T. Reisner, G. Clifford, L. Lehman, G.B. Moody, T. Heldt, T.H. Kyaw, B.E. Moody, R.G. Mark.Multiparameter intelligent monitoring in intensive care II (MIMIC-II): A public-access ICU database. Critical Care Medicine 39(5):952-960 (2011 May); doi: 10.1097/CCM.0b013e31820a92c6.

[2] Goldberger AL, Amaral LAN, Glass L, Hausdorff JM, Ivanov PCh, Mark RG, Mietus JE, Moody GB, Peng C-K, Stanley HE. PhysioBank, PhysioToolkit, and PhysioNet: Components of a New Research Resource for Complex Physiologic Signals.Circulation 101(23):e215-e220 [Circulation Electronic Pages; http://circ.ahajournals.org/cgi/content/full/101/23/e215]; 2000 (June 13).

 

Author: johnrzaleski_eqbr0v

John R. Zaleski, PhD, CAP, CPHIMS, is Chief Analytics Officer of Bernoulli, a leader in real-time connected healthcare. Dr. Zaleski brings 21 years of experience in researching and ushering to market devices and products to improve healthcare. He received his PhD from the University of Pennsylvania, with a dissertation that describes a novel approach for modeling and prediction of post-operative respiratory behavior in post-surgical cardiac patients. Dr. Zaleski has a particular expertise in designing, developing, and implementing clinical and non-clinical point-of-care applications for hospital enterprises. Dr. Zaleski is the named inventor or co-inventor on seven issued patents related to medical device interoperability. He is the author of numerous peer-reviewed articles on clinical use of medical device data, information technology and medical devices and wrote three seminal books on integrating medical device data into electronic health records and the use of medical device data for clinical decision making, including the #1 best seller of HIMSS 2015 on connected medical devices.

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