Filtering of Arterial Blood Pressure Signal Artifact using the Extended Kalman Filter
In an earlier post, I had discussed some mathematical techniques for mitigating alarm fatigue.
Expanding on the mathematical techniques employed, another reason for filtering of data includes the smoothing of artifact or spikes that are due to signal errors or other issues associated with signal acquisition.
Figure 1 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:
 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.
 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).