Processing of pulse oximeter data using discrete wavelet analysis. Academic Article

abstract

• A wavelet-based signal processing technique was employed to improve an implantable blood perfusion monitoring system. Data was acquired from both in vitro and in vivo sources: a perfusion model and the proximal jejunum of an adult pig. Results showed that wavelet analysis could isolate perfusion signals from raw, periodic, in vitro data as well as fast Fourier transform (FFT) methods. However, for the quasi-periodic in vivo data segments, wavelet analysis provided more consistent results than the FFT analysis for data segments of 50, 10, and 5 s in length. Wavelet analysis has thus been shown to require less data points for quasi-periodic data than FFT analysis making it a good choice for an indwelling perfusion monitor where power consumption and reaction time are paramount.

authors

• Cote, Gerard

published proceedings

• IEEE Trans Biomed Eng

author list (cited authors)

• Lee, S., Ibey, B. L., Xu, W., Wilson, M. A., Ericson, M. N., & Cot, G. L.

citation count

• 23

complete list of authors

• Lee, Seungjoon||Ibey, Bennett L||Xu, Weijian||Wilson, Mark A||Ericson, M Nance||Coté, Gerard L

publication date

• July 2005

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

keywords

• Algorithms
• Animals
• Blood Flow Velocity
• Diagnosis, Computer-Assisted
• Fourier Analysis
• Oximetry
• Pulsatile Flow
• Reproducibility Of Results
• Sensitivity And Specificity
• Signal Processing, Computer-Assisted
• Swine

Digital Object Identifier (DOI)

• 10.1109/TBME.2005.847538

start page

• 1350

end page

• 1352

volume

• 52

issue

• 7

URL

• http%3A%2F%2Fdx.doi.org%2F10.1109%2Ftbme.2005.847538