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Pattern Recognition in Electroencephalography

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Pattern Recognition

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Abstract

When large numbers of nerve cells in the surface layers of the brain are involved in synchronous electrical activity the signals produced can be picked up by electrodes applied to the surface of the scalp. The activity recorded, which is termed the electroencephalogram (EEG), has an amplitude generally of some 10–100 μV and is usually recorded in a frequency band from 0.5 to 50 Hz. The EEG is studied for a variety of purposes and can be used as an aid to the diagnosis of structural diseases or functional disorders of the brain or as a research tool in human psychology and psychopharmacology. For a standard introductory textbook of electroencephalography and as a source of key references, the reader should consult Kiloh et al. (1972).

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References

  • Baldock, G. R., and Walter, W. G., 1946, A new electronic analyser, Electron. Eng. 18: 339–342.

    Google Scholar 

  • Batchelor, B. G., 1969, Learning Machines for Pattern Recognition, Ph.D. thesis, University of Southampton.

    Google Scholar 

  • Batchelor, B. G., 1974, Practical Approach to Pattern Classification, Plenum Press, London and New York.

    Google Scholar 

  • Batchelor, B. G., and Hand, D. J., 1975, On the graphical analysis of pdf estimators for pattern recognition, Kybernetes 4: 239–246.

    Article  Google Scholar 

  • Bickford, R. G., 1973, Application of compressed spectral array in clinical EEG. In: Automation of Clinical Electroencephalography (P. Kellaway and I. Petersen, eds.), p. 318, Raven Press, New York.

    Google Scholar 

  • Bickford, R. G., Fleming, N. I., and Billinger, T. W., 1971, Compression of EEG data by isometric power spectral plots, Electroenceph. Clin. Neurophysiol. 31: 631–636.

    Article  Google Scholar 

  • Binnie, C. D., 1975, A comparison of different methods of period analysis, Electroenceph. Clin. Neurophysiol. 38: 662.

    Google Scholar 

  • Binnie, C. D., MacGillivray, B. B., and Osselton, J. W., 1974, Traditional methods of examination in clinical neurophysiology. In: Handbook of Electroencephalography and Clinical Neurophysiology, 3C (A. Remond, ed.), Elsevier, Amsterdam, p. 126.

    Google Scholar 

  • Binnie, C. D., Prior, P. F., Lloyd, D. S. L., Scott, D. F., and Margerison, J. H., 1970, Electro-encephalographic prediction of fatal anoxic brain damage after resuscitation from cardiac arrest, Brit. Med. J. IV: 265–268.

    Article  Google Scholar 

  • Cooley, J. W., and Tukey, J. W., 1965, An algorithm for the machine calculation of complex fourier series, Math. Computation 19: 297–301.

    Article  Google Scholar 

  • Cooper, R., Osselton, J. W., and Shaw, J. C, 1974, EEG Technology, Butterworths, London.

    Google Scholar 

  • Dietsch, G., 1932, Fourier analyse von Electroenkephalogrammen des Menschen, Pflüger’s Arch. 230: 106–112.

    Article  Google Scholar 

  • Dixon, W. J., 1970, BMDø7M-stepwise discriminant analysis. In: Bio-medical Computer Programs, University of California Press, San Francisco, Calif.

    Google Scholar 

  • Donchin, E., 1969, Discriminant analysis in average evoked response studies: The study of single trial data, Electroenceph. Clin. Neurophysiol. 27: 311–314.

    Article  CAS  Google Scholar 

  • Dumermuth, G., and Keller, E., 1973, EEG spectral analysis by means of fast Fourier transform. In: Automation of Clinical Electroencephalography (P. Kellaway and I. Paterson, eds.), Raven Press, New York.

    Google Scholar 

  • Frost, J. D., 1970, An automatic sleep analyser, Electroenceph. Clin. Neurophysiol. 29: 88–92.

    Article  Google Scholar 

  • Fukunaga, K., 1972, An Introduction to Statistical Pattern Recognition, Academic Press, New York.

    Google Scholar 

  • Gotman, J., Skuce, D. R., Thompson, C. J., Gloor, P., Ives, J. R., and Ray, W. F., 1973, Clinical applications of spectral analysis and extraction of features from electroencephalograms with slow waves in adult patients, Electroenceph. Clin. Neurophysiol. 35: 225–235.

    Article  CAS  Google Scholar 

  • Botman, J. R., Gloor, P., and Ray, W. F., 1975, A quantitative comparison of traditional reading of the EEG and interpretation of computer-extracted features in patients with superatentorial brain lesions, Electroenceph. Gin. Neurophysiol. 38: 623–639.

    Article  Google Scholar 

  • Hjörth, B., 1970, EEG analysis based on time-domain properties, Electroenceph. Clin. Neurophysiol. 29: 306–310.

    Article  Google Scholar 

  • Hjörth, B., 1973, The physical significance of time-domain descriptors in EEG analysis, Electroenceph. Clin. Neurophysiol. 34: 321–325.

    Article  Google Scholar 

  • Itil, T. M., 1974, Modern Problems of Pharmacopsychiatry: Eight Psychotropic Drugs and the Human EEG, Karger, Basel, München, p. 337.

    Google Scholar 

  • Lee, R. C. T., 1974, Sub-minimal spanning tree approach for large data clustering, Proc. 2nd Int. Jt. Conf. Pattern Recognition, Copenhagen, p. 22.

    Google Scholar 

  • Kellaway, P., 1973, Automation of clinical electroencephalography: the nature and scope of the problem. In: Automation of Ginical Electroencephalography, (P. Kellaway and I. Petersen, eds.), Raven Press, New York, p. 318.

    Google Scholar 

  • Kiloh, L. G., McComas, A. J. and Osselton, J. W., 1972, Clinical Electroencephalography, Butterworths, London, p. 239.

    Google Scholar 

  • Larsen, L. E., and Walter, D. O., 1970, On automatic methods of sleep staging by EEG spectra, Electroenceph. Clin. Neurophysiol. 28: 459–467.

    Article  CAS  Google Scholar 

  • Lloyd, D. S. L., Binnie, C. D., and Batchelor, B. G., 1972. Pattern recognition in EEG. In: Interdisciplinary Investigation of the Brain (J. P. Nicholson, ed.), Plenum Press, London.

    Google Scholar 

  • Martin, W. B., Johnson, L. C., Viglione, S. S., Naitoh, P., Joseph, R. D., and Moses, J. D., 1972, Pattern recognition of EEG-EOG as a technique for all-night sleep stage scoring Electroenceph. Clin. Neurophysiol. 32: 417–427.

    Article  CAS  Google Scholar 

  • Matousek, M., and Petersen, I., 1973a, Frequency analysis of the EEG in normal children and adolescents. In: Automation of Clinical Electroencephalography (P. Kellaway and I. Petersen, eds.), Raven Press, New York, p. 318.

    Google Scholar 

  • Matousek, M., and Petersen, I., 1973b, Automatic evaluations of EEG background activity by means of age-dependent EEG quotients, Electroenceph. Clin. Neurophysiol. 35: 603–612.

    Article  CAS  Google Scholar 

  • Maynard, D. E., and Prior, P. F., 1973, A predictive instrument to assist with interprediction of EEGs of patients resuscitated after cardiac arrest, Electroenceph. Clin. Neurophysiol. 34: 744.

    Google Scholar 

  • Prior, P. F., 1973, The EEG in Acute Cerebral Anoxia, Exerpta Medica, Amsterdam.

    Google Scholar 

  • Rechtschaffen, A., and Kales, A., 1968, A Manual of Standardized Terminology Techniques and Scoring System for Sleep Stages of Human Subjects, U.S. Government Printing Office, Washington, D. C.

    Google Scholar 

  • Saltzberg, B., Burch, N. R., McLennan, M. A., and Correll, E. G., 1957, A new approach to signal analysis in electroencephalography, IRE Trans. Med. Electron., 8: 24.

    Article  Google Scholar 

  • Sammon, J. W., 1969, Non-linear mapping for data structure analysis, Trans. IEEE C-18: 401.

    Google Scholar 

  • Serafini, M., 1973, A pattern recognition method applied to EEG analysis, Computers Biomed. Res. 16: 187–195.

    Article  Google Scholar 

  • Sklar, B., Hanley, J., and Simmons, W. W., 1973, A computer analysis of EEG spectral signatures for normal and dyslexic children, IEEE Trans. Biomed. Eng. 20: 20–26.

    Article  CAS  Google Scholar 

  • Smith, J. R., and Karacan, I., 1971, EEG sleep-stage scoring by an automatic hybrid system, Electroenceph. Clin. Neurophysiol. 31: 231–237.

    Article  CAS  Google Scholar 

  • Viglione, S. S., 1970, Applications of pattern recognition technology. In: Adaptive Learning and Pattern Recognition Systems: Theory and Applications (J. M. Mendal and K. S. Fu, eds.), Academic Press, New York, pp. 115–162.

    Chapter  Google Scholar 

  • Walter, D. O., 1963, Spectral analysis for electroencephalograms: Mathematical determination of neurophysiological relationships from records of limited duration, Exp. Neurol. 8: 155–181.

    Article  CAS  Google Scholar 

  • Walter, D. O., Rhodes, J. M., and Adey, W. R., 1967, Discriminating among states of consciousness by EEG measurements, a study of four subjects, Electroenceph. Clin. Neurophysiol. 22: 22–29.

    Article  CAS  Google Scholar 

  • Wennberg, A., and Zetterberg, L. H., 1971, Application of a computer-based model for EEG analysis, Electroenceph. Clin. Neurophysiol. 31: 457–468.

    Article  CAS  Google Scholar 

  • Wilks, S. S., 1962, Mathematical Statistics, Wiley, New York.

    Google Scholar 

  • Zahn, C. T., 1971, Graph-theoretical methods for detecting and describing Gestalt clusters, Trans. IEEE C-20: 68.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Instituut voor Epilepsiebestrijding, Heemstede, Netherlands

    C. D. Binnie

  2. Neuropsychology Unit, Department of Applied Psychology, University of Aston, Birmingham, England

    G. F. Smith

  3. Department of Electronics, University of Southampton, Southampton, England

    B. G. Batchelor

Authors
  1. C. D. Binnie
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  2. G. F. Smith
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  3. B. G. Batchelor
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Editor information

Editors and Affiliations

  1. University of Southampton, England

    Bruce G. Batchelor

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© 1978 Plenum Press, New York

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Binnie, C.D., Smith, G.F., Batchelor, B.G. (1978). Pattern Recognition in Electroencephalography. In: Batchelor, B.G. (eds) Pattern Recognition. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-4154-3_15

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  • DOI: https://doi.org/10.1007/978-1-4613-4154-3_15

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4613-4156-7

  • Online ISBN: 978-1-4613-4154-3

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