« PreviousContinue »
United States Patent  [ii] Patent Number: 5,458,117
Chamoun et al.  Date of Patent: Oct. 17,1995
 CEREBRAL BIOPOTENTIAL ANALYSIS SYSTEM AND METHOD
 Inventors: Nassib G. Chamoun, Dedham; Jeffrey C. Sigl, Ashland; Charles P. Smith,
Framingham, all of Mass.
 Assignee: Aspect Medical Systems, Inc., Natick, Mass.
 Appl. No.: 257,356
 Filed: Jun. 9,1994
Related U.S. Application Data
 Continuation-in-part of Ser. No. 782,636, Oct. 25,1991, Pat. No. 5,320,109.
 Int. CI.6 A61B 5/05
 U.S. CI 128/734
 Field of Search 128/731, 732,
128/734, 733, 635; 364/413.01, 413.02, 413.03, 413.04, 413.05, 413.06
 References Cited
U.S. PATENT DOCUMENTS
3,863,625 2/1975 Viglione et al 128/732
4,407,299 10/1983 Culver 128/731
4,557,270 12/1985 John 128/731
4,697,598 10/1987 Bernard et al 128/731
4,705,049 11/1987 John 128/731
4,753,246 6/1988 Freeman 128/731
4,846,190 7/1989 John 128/731
4,905,285 2/1990 Allen et al 128/419 R
4,907,597 3/1990 Chamoun 128/731
4,974,602 12/1990 Abraham-Fuchs et al 128/731
5,010,891 4/1991 Chamoun 128/731
Withington, PS., Morton, J., Arnold, R., Sebel, PS., and Moberg, R. Assessment of power spectral edge for monitoring depth of anesthesia using low methohexitone infusion. Int-J-Clin-Monit-Computing. 3(2): pp. 117-122 (1986).
Whitton, Genetic Dependence of the Electroencephalogram
Disclosed is a system and method to derive a diagnostic index indicative of a selected cerebral phenomena which obtains 19 unipolar EEG signals from regions of interest on both the left and right hemispheres of a subject's brain. The system uses high-gain, low-noise amplifiers to maximize the dynamic range for low energy wave components of the signals. Band-pass filtering is used to reduce noise and to avoid aliasing. The system applies commonly used digital signal processing (DSP) techniques to digitize, to low-pass filter (100 Hz), and to decimate the signals. Power spectral, bispectral, and higher-order spectral processing is then performed. In a preferred embodiment, the system divides the most recent 63 seconds of digitized EEG data from each lead into 60 4-second intervals, each with 3 seconds of overlap with the previous interval. For a selected set of derived leads, the system produces auto power spectrum, autobispectrum, and auto higher-order spectrum variables, by using either a Fast Fourier Transform (FFT) based approach or a parametric approach. Any pair of leads can be combined to compute cross power spectrum, cross bispectrum, and cross higher-order spectrum variables. The spectral values are separated into bins and a value representative of the bin is selected or computed and then each value is multiplied by a predetermined coefficient. The resulting products are summed to arrive at the diagnostic index.
22 Claims, 14 Drawing Sheets
Brillinger, D. R. An introduction to polyspectra. Annals of Mathematical Statistics 36:1351-1374 (1965). Russ, W., Kling, D., Krumholz, W., Fraedrich, G., and Hempelmann, G., [Experience with a new EEG spectral analyzer in carotid surgery] Erfahrungen mit einem neuen EEG-Spektralanalysator in der Karotischirurgie. Anaesthetist 34(2): pp. 85-90 (1985).
Rampil, I. J., Holzer, J. A., Quest, D. O., Rosenbaum, S. H., and Correll J. W., Prognostic value of computerized EEG analysis during carotic endarterectomy. Anesthesia Analgesia 62:186-92 (1983).
Huber, P. J., B. Kleiner, T. Gasser and G. Dumermuth. Statistical method for investigating phase relations in stationary stochastic processes. IEEE Trans. Aud. & Electroacou. AU-19/l:78-86 (1971).
Tryon, P. V. The bispectrum and higher-order spectra: A bibliography. US NBS (Tech Note 1036) (1981). Nikias, C. L., and Raghuveer, M. R. Bispectrum estimation: A digital signal processing framework. Proc. IEEE. 75,7:869-91 (1987).
Susumu, T. and Osamu, T. Analysis of wave shapes of alpha waves on EEG by means of the bispectrum. (1973). Kleiner, B., Huber, P. J., and Dumermuth, G. Analysis of the interelations between frequency bands of the EEG by means of the bispectrum. Electroencephalogr. Neurophysiol. 27(7): 693-694 (1969).
Dumermuth, G., Huber, P. J., Kleiner, B., and Gasser, T. Analysis of the interrelations between frequency bands of the EEG by means of the bispectrum. A preliminary study. Electroencephalogr. Clin. Neurophysiol. 31(2):137—148 (1971).
Barnett, T. P., Johnson, L. C, Naitoh, P., Hicks, N. and Nute, C, Bispectrum analysis of electroencephalogram signals during waking and sleeping. Science 172:402-401 (1971). Raghuveer, M. R. and Nikias, C. L. Bispectrum estimation: A parametric approach. IEEE Trans, on Acoustics, Speech & Signal Processing. 33:1213-1230 (1985). Volavka, J., Matousek, M., Feldstein, S. et al. The reliability of electroencephalography assesement. Electroencephalography and Electromyography. 4: 123 (1973). Eichhorn, J. H., Cooper, J. B., Cullen, D. J., Ward, M. R., Philip, J. H., and Seeman, R. G. Standards for patient monitoring during anesthesia at Harvard Medical School. JAMA. 256(8): pp. 1017-1020 (1986). Jasper, H. H. The ten-twenty electrode system of the international federation in electroencephalography and clinical neurophysiology. EEG Journal. 10:371-375 (1985). Haykin, S. Adaptive filter theory. Prentice-Hall, Englewood Cliffs, N.J. (1986).
Proceedings of the Fourteenth Annual Northeast Bioengineering Conference, IEEE, New York, US 10 Mar. 1988, Durham, N.H., pp. 198-203, XP000093434, Ning et al, "Detecting Biphase Coupling of Sleep EEG Via Bispectra". IEEE Transactions on Biomedical Engineering, IEEE, New York, vol. 36, No. 4, Apr. 4, 1989, pp. 497-499, Ning et al, "Bispectral Analysis of the Rat EEG During Various Vigilance States".
IEEE Engineering in Medicine & Biology Society 10th Annual Conference.
IEEE, New York, vol. 3/4, Nov. 4, 1988, New Orleans, pp. 1218-1219, Ning et al, "Bispectral Analysis of Rat EEG During Maturation".