Adaptive Modeling and Spectral Estimation of Nonstationary Biomedical Signals Based on Kalman Filtering

M. Aboy, O.W. Marquez, J. McNames, R. Hornero, T. Trong, B. Goldstein
2005 IEEE Transactions on Biomedical Engineering  
We describe an algorithm to estimate the instantaneous power spectral density (PSD) of nonstationary signals. The algorithm is based on a dual Kalman filter that adaptively generates an estimate of the autoregressive model parameters at each time instant. The algorithm exhibits superior PSD tracking performance in nonstationary signals than classical nonparametric methodologies, and does not assume local stationarity of the data. Furthermore, it provides better time-frequency resolution, and is
more » ... robust to model mismatches. We demonstrate its usefulness by a sample application involving PSD estimation of intracranial pressure signals (ICP) from patients with traumatic brain injury (TBI). Index Terms-Intracranial pressure, Kalman filter, linear models, spectral estimation, traumatic brain injury.
doi:10.1109/tbme.2005.851465 pmid:16119245 fatcat:yj73yriqpbgw5ebu6fy3g76zva