Identification of physiological systems using pseudo-inverse based deconvolution

Author

Westwick, David T. ; Kearney, Robert E.

Author_Institution

Dept. of Biomed. Eng., McGill Univ., Montreal, Que., Canada

Volume

2

fYear

1995

fDate

20-23 Sep 1995

Firstpage

1405

Abstract

The identification of nonparametric impulse response functions (IRFs) from noisy, finite-length data records is analyzed using the techniques of matrix perturbation analysis. Based on these findings, we develop a new method for IRF estimation which is expected to be more robust than existing techniques, particularly when the input is non-white. An application to the identification of human ankle dynamics is presented which demonstrates the superiority of this new method over classical techniques

Keywords

Toeplitz matrices; biomechanics; deconvolution; identification; inverse problems; perturbation techniques; physiological models; transient response; Toeplitz structured autocorrelation matrix; human ankle dynamics; identification; matrix perturbation analysis; noisy finite-length data records; nonparametric impulse response functions; nonwhite input; physiological systems; pseudo-inverse based deconvolution; Autocorrelation; Biomedical measurements; Data analysis; Deconvolution; Humans; Linear systems; Matrix decomposition; Nonlinear dynamical systems; Nonlinear systems; Robustness;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 1995., IEEE 17th Annual Conference

Conference_Location

Montreal, Que.

Print_ISBN

0-7803-2475-7

Type

conf

DOI

10.1109/IEMBS.1995.579749

Filename

579749