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Cardiac Doppler blood-flow signal analysis

Part 2 time/frequency representation based on autoregressive modelling

  • Physiological Measurement
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Abstract

Doppler spectrograms obtained by using autoregressive (AR) modelling based on the Yule-Walker equations were investigated. A complex AR model using the in-phase and the quadrature components of the Doppler signal was used to provide blood-flow directions. The effect of model orders on the spectrogram estimation was studied using cardiac Doppler blood flow signals taken from 20 patients. The ‘final prediction error’ (FPE) and the ‘Akaike's information criterion’ (AIC) provided almost identical results in model-order selection. An index, the spectral envelope area (SEA), was used to evaluate the effect of window duration and sampling frequency on AR Doppler spectrogram estimation. The statistical analysis revealed that the SEA obtained from AR modelling was not sensitive to window duration and sampling frequency. This result verified the consistency of the AR Doppler spectrogram. The white-noise characteristics of the AR modelling error signal indicated that the Doppler blood-flow signal can be adequately modelled as a complex AR process. With appropriate model orders, AR modelling provided better Doppler spectrogram estimates than the periodogram.

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Authors and Affiliations

  1. Biomedical Engineering Laboratory, Clinical Research Institute of Montreal, 110 West Pine Avenue, H2W 1R7, Montreal, Quebec, Canada

    Z. Guo, L. -G. Durand, L. Allard & G. Cloutier

  2. Department of Electrical Engineering, McGill University, 3480 University Street, H3A 2A7, Montreal, Quebec, Canada

    Z. Guo & H. C. Lee

  3. Noninvasive Cardiovascular Research Laboratory, Hotel-Dieu de Montreal Hospital, 3840 St-Urbain, H2W 1T8, Montreal, Quebec, Canada

    L. Allard & Y. E. Langlois

Authors
  1. Z. Guo
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  2. L. -G. Durand
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  3. L. Allard
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  4. G. Cloutier
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  5. H. C. Lee
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  6. Y. E. Langlois
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Guo, Z., Durand, L.G., Allard, L. et al. Cardiac Doppler blood-flow signal analysis. Med. Biol. Eng. Comput. 31, 242–248 (1993). https://doi.org/10.1007/BF02458043

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  • DOI: https://doi.org/10.1007/BF02458043

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