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Method and apparatus for transcranial doppler sonography

Patent 5379770 Issued on January 10, 1995. Estimated Expiration Date: Icon_subject December 21, 2013. Estimated Expiration Date is calculated based on simple USPTO term provisions. It does not account for terminal disclaimers, term adjustments, failure to pay maintenance fees, or other factors which might affect the term of a patent.

Patent References

Ultrasonic doppler diagnostic system using pattern recognition Patent #: 4770184
Issued on: 09/13/1988
Inventor: Greene, Jr. ,   et al.

Inventor

Application

No. 172594 filed on 12/21/1993

US Classes:

600/455Pulse Doppler

Examiners

Primary: Jaworski, Francis J.

Attorney, Agent or Firm

International Class

A61B 008/06

Abstract

The effect of noise in the displayed information obtained from transcranial Doppler measurements is reduced by estimating the spectra of the returned Doppler signal as the average of Fourier spectra computed using multiple windows for the data being analyzed. The windows are chosen so that the spectra from different windows are approximately statistically independent, thereby reducing the variance of the spectrum by the averaging process. The Doppler data may be obtained by applying repeated pulses of ultrasonic energy to the head of a subject and isolating the Doppler frequency components of the return signal to obtain a set of data from a selected number of pulses. The data set so obtained has the multiple window functions applied thereto to obtain multiple windowed data sets which are operated on, as in a digital signal processor, to obtain multiple discrete Fourier transforms of the windowed data sets. A power spectrum is estimated as the averaged sum of the squares of the magnitudes of each of the discrete Fourier transforms. The spectra obtained from data sets gathered in sequence may be displayed to an operator to show the spectral content of the return signal over time, which corresponds to the velocity of blood flow at a position within the head of the subject as a function of time.

Other References

  • Knox, R. A. et al "Computer Based Classification of Carotid Arterial Disease: A Prospective Assessment" Stroke vol. 13, No. 5 Sep.-Oct. 1982 pp. 589-594
  • David J. Thomson, "Spectrum Estimation and Harmonic Analysis", Proceedings of the IEEE, vol. 70, No. 9, Sep. 1982, pp. 1055-1096
  • R. Aaslid, "The Doppler Principle Applied to Measurement of Blood Flow Velocity in Cerebral Arteries," Chap. 3, pp. 22-38, in Transcranial Doppler Sonography(book), R. Aaslid, Ed., Springer-Verlag, Wien, New York, 1986
  • Thomas P. Bronez, "Spectral Estimation of Irregularly Sampled Multi-dimensional Processes by Generalized Prolate Spheroidal Sequences," IEEE Trans. on Acoustics, Speech, and Signal Processing, vol. 36, No. 12, Dec. 1988, pp. 1862-1873
  • N. Levanon, Radar Principles (book), Chap. 10, "Processing a Coherent Pulse Train", pp. 202-218, Wiley Inter-Science 1988
  • Barry C. Van Veen, et al., "Estimation of Structured Covariance Matrices and Multiple Window Spectrum Analysis," IEEE Trans. on Acoustics, Speech, and Signal Processing, vol. 38, No. 8, Aug. 1990, pp. 1467-1472
  • C. T. Mullis, et al., "Quadratic Estimators of the Power Spectrum," Chap. 1, pp. 1-57, in Advances in Spectrum Analysis and Array Processing, vol. 1 (book), S. Haykin, Ed., Prentice Hall, Englewood Cliffs, N.J., 1991
  • Tsung-Ching Liu, et al., "Multiple Window Based Minimum Variance Spectrum Estimation for Multidimensional Random Fields," IEEE Trans. on Signal Processing, vol. 40, No. 3, Mar. 1992, pp. 578-589
  • A. Drosopoulos, et al., "Adaptive Radar Parameter Estimation with Thomson's Multiple-Window Method," Chap. 7, pp. 381-461, in Adaptive Radar Detection and Estimation, S. Haykins, et al., Eds., Wiley, New York, 1992
  • TC 2000S Transcranial Doppler System Service Handbook, Eden Medizinische Elektronik, GmbH, Aug. 1990
  • TC 2000 Transcranial Doppler System Operator's Handbook, Eden Medical Electronics, GmbH, May 199
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