Name
Title | ||
|---|---|---|
A novel method for nonstationary power spectral density estimation of cardiovascular pressure signals based on a Kalman filter with variable number of measurements. |
Abstract | ||
|---|---|---|
We present a novel parametric power spectral density (PSD) estimation algorithm for nonstationary signals based on a Kalman filter with variable number of measurements (KFVNM). The nonstationary signals under consideration are modeled as time-varying autoregressive (AR) processes. The proposed algorithm uses a block of measurements to estimate the time-varying AR coefficients and obtains high-resolution PSD estimates. The intersec- tion of confidence intervals (ICI) rule is incorporated into the algorithm to generate a PSD with adaptive window size from a series of PSDs with different number of measure- ments. We report the results of a quantitative assessment study and show an illustrative example involving the application of the algorithm to intracranial pressure signals (ICP) from patients with traumatic brain injury (TBI). |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/s11517-008-0351-x | Med. Biol. Engineering and Computing |
Keywords | Field | DocType |
kalman filter,autoregressive process,confidence interval,high resolution,power spectral density,spectral density | Autoregressive model,Computer vision,Cardiovascular Pressure,Algorithm,Kalman filter,Speech recognition,Spectral density,Parametric statistics,Artificial intelligence,Quantitative assessment,Confidence interval,Mathematics | Journal |
Volume | Issue | ISSN |
46 | 8 | 1741-0444 |
Citations | PageRank | References |
3 | 0.45 | 4 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Z. G. Zhang | 1 | 134 | 15.08 |
| K. M. Tsui | 2 | 173 | 16.60 |
| Shing-Chow Chan | 3 | 4 | 0.81 |
| Winnie W. Y. Lau | 4 | 64 | 7.03 |
| M. Aboy | 5 | 3 | 0.45 |