Secondary wavelet feature decoupling (SWFD) and its use in detecting patient respiration from the photoplethysmogram

Author

Addison, P.S. ; Watson, J.N.

Author_Institution

Fac. of Eng. & Comput., Napier Univ. of Edinburgh, UK

Volume

3

fYear

2003

fDate

17-21 Sept. 2003

Firstpage

2602

Abstract

We describe a method for the identification of time-frequency features associated with patient respiration in the wavelet decomposition of the photoplethysmogram where the respiration features are masked by other signal components with similar spectral content. In the novel methodology a secondary transform is performed on a signal derived from the original wavelet decomposition in the region of the pulse band. The method has wide application to many other problematic signals.

Keywords

feature extraction; medical signal processing; patient diagnosis; patient monitoring; plethysmography; pneumodynamics; time-frequency analysis; patient respiration detection; photoplethysmogram; respiration features; secondary wavelet feature decoupling; time-frequency features identification; wavelet decomposition; Biomedical signal processing; Data mining; Equations; Feature extraction; Signal analysis; Signal processing; Surface waves; Time frequency analysis; Wavelet analysis; Wavelet transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2003. Proceedings of the 25th Annual International Conference of the IEEE

ISSN

1094-687X

Print_ISBN

0-7803-7789-3

Type

conf

DOI

10.1109/IEMBS.2003.1280448

Filename

1280448