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Estimation of signal-to-noise ratio of a quasiperiodic cardiovascular signal using coherency and correlation techniques

  • Computing and Data Processing
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Abstract

Two algorithms, based on coherency and correlation functions, are proposed for estimating the signal-to-noise ratio of physiological signals including the effect of flicker noise. New sampling techniques based on converting a single continuous signal into two time series that satisfy the requirements of the algorithms are proposed. The algorithms are applied to a computer-generated signal and noise composite of known SNR, as well as to quasiperiodic left ventricular pressure (LVP) waveforms transduced from ten patients. Both coherency and correlation methods were used to estimate the known SNR of the computer-generated compsite, signal and noise to within ±5 per cent, for SNR values between 10 and 30 dB. When applied to LVP waveforms, the two methods gave SNR values which were almost identical. Flicker noise associated with the LVP waveforms was computed to be 14 dB higher than the white noise. It is concluded that flicker, or 1/f noise, which has been heretofore ignored in SNR calculations of pressure and flow signals, must now be included.

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References

  • Beduchamp, K. andYuen, C. (1979)Digital methods for signal analysis. George Allen & Unwin, London.

    Google Scholar 

  • Benignus, V. A. (1969a) Estimation of the coherence spectrum and its confidence interval using the fast Fourier transform.IEEE Trans.,AU-17, 145–150.

    Google Scholar 

  • Benignus, V. A. (1969b) Estimation of coherence, spectrum of non-Gaussian time series populations.,AU-17, 198–201.

    Google Scholar 

  • Carter, G. C., Knapp, C. H. andNuttall, A. H. (1973) Estimation of the magnitude-squared coherence function via overlapped fast Fourier transform processing.,AU-21, 337–344.

    Google Scholar 

  • Carter, G. C. andKnapp, C. H. (1975) Coherence and its estimation via the partitioned modified chirp-Z transform.,ASSP-23, 257–264.

    Google Scholar 

  • Charayaphan, C. (1987) Selection, implementation, and testing of an efficient algorithm for real-time computation of signal-to-noise ratio of physiological signals. Master Thesis, Technical University of Nova Scotia, 14–16.

  • De Boer, L. W. V., Nosta, J. J., Kloner, R. A. andBrunwald, E. (1982) Studies of Amiodarone during experimental myocardial infarction; beneficial effects on hemodynamics and infarct size.Circ.,65, 508–512.

    Google Scholar 

  • Fay, J. W. (1980) Comfidence bounds for signal-to-noise ratios from magnitude-squared coherence estimates.IEEE Trans.,ASSP-28, 758–760.

    Google Scholar 

  • Fink, D. G. andChristiansen, D. (1982)Electronics Engineers' Handbook, 2nd edn. McGraw-Hill, New York.

    Google Scholar 

  • Kornreich, F., Rautaharju, P. M., Warren, J. W., Horacek, B. M. andDramaix, M. (1985) Effective extraction of diagnostic ECG waveform information using orthonormal basic functions derived from body surface potential maps.J. Electrocardiol.,18, 341–350.

    Google Scholar 

  • Kornreich, F., Montague, J. J., Rautaharju, P. M., Block, P., Warren, J. W. andHoracek, B. M. (1986) Identification of best electrocardiographic leads for diagnosing anterior and inferior myocardial infarction by statistical analysis of body surface potential maps.Am. J. Cardiol.,58, 863–871.

    Article  Google Scholar 

  • Mirsky, I., Dharjoy, N. andSandler, H. (1974)Cardiac mechanics: physiological, clinical and mathematical considerations. Wiley, New York, 102–107.

    Google Scholar 

  • Oppenheim, A. V. andSchaeer, R. W. (1975)Digital signal processing. Prentice-Hall, Inc., New York.

    Google Scholar 

  • Scannell, E. H. andCarter, G. C. (1975) Confidence bounds for magnitude-squared coherence estimates.IEEE Trans.,ASSP-26, 475–477.

    Google Scholar 

  • Soderquist, D. (1979) Minimization of noise in operational amplifier applications. InPMI Data Book.PMI, 15/43-15/51.

  • Stoisiek, M. andWolf, D. (1980) Origin of 1/f noise in bipolar transistors.IEEE Trans.,ED-27, 1753–1757.

    Google Scholar 

  • Suh, C. H. (1981) A new theory of g-r and 1/f nois.,ED-28, 1555–1557.

    Google Scholar 

Download references

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Charayaphan, C., Marble, A.E., Nugent, S.T. et al. Estimation of signal-to-noise ratio of a quasiperiodic cardiovascular signal using coherency and correlation techniques. Med. Biol. Eng. Comput. 27, 572–579 (1989). https://doi.org/10.1007/BF02441638

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