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Real-time change detection of steady-state evoked potentials

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Abstract

Steady-state evoked potentials (SSEP) are the electrical activity recorded from the scalp in response to high-rate sensory stimulation. SSEP consist of a constituent frequency component matching the stimulation rate, whose amplitude and phase remain constant with time and are sensitive to functional changes in the stimulated sensory system. Monitoring SSEP during neurosurgical procedures allows identification of an emerging impairment early enough before the damage becomes permanent. In routine practice, SSEP are extracted by averaging of the EEG recordings, allowing detection of neurological changes within approximately a minute. As an alternative to the relatively slow-responding empirical averaging, we present an algorithm that detects changes in the SSEP within seconds. Our system alerts when changes in the SSEP are detected by applying a two-step Generalized Likelihood Ratio Test (GLRT) on the unaveraged EEG recordings. This approach outperforms conventional detection and provides the monitor with a statistical measure of the likelihood that a change occurred, thus enhancing its sensitivity and reliability. The system’s performance is analyzed using Monte Carlo simulations and tested on real EEG data recorded under coma.

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References

  • Bach MMT, Meigen T (1999) Do’s and don’ts in fourier analysis of steady-state potentials. Doc Ophthalmol 99: 69–82

    Article  PubMed  CAS  Google Scholar 

  • Basseville M, Nikiforov IV (1993) Detection of abrupt changes: theory and applications. Prentice-Hall, Englewood Cliffs

    Google Scholar 

  • Bender R, Schultz B, Schultz A, Pichlmayr I (1992) Testing the gaussianity of the human eeg during anasthesia. Methods Inf Med 31(1): 56–59

    PubMed  CAS  Google Scholar 

  • Bergholz R, Lehmann TN, Fritz G, Ruther K (2008) Fourier transformed steady-state flash evoked potentials for continuous monitoring of visual pathway function. Doc Ophthalmol 116: 217–229

    Article  PubMed  CAS  Google Scholar 

  • Burke D, Nuwer M, Daube J, Fischer C, Schramm J, Yingling CD, Jones S (1999) Intraoperative monitoring. Electroencephalogr Clin Neurophysiol 52: 133–148

    CAS  Google Scholar 

  • Chiappa K (1997) Evoked potentials in clinical medicine. Lippincott-Raven, Philadelphia

    Google Scholar 

  • Davila C, Srebro R (2000) Subspace averaging of steady-state visual evoked potentials. IEEE Trans Bio-Med Eng 47: 720–728

    Article  CAS  Google Scholar 

  • Davilla C, Ghaleb I, Serebro R (1997) Prewhitening of background brain activity via autoregressive modeling. Biomedical engineering conference, 1997, Proceedings of the 1997 sixteenth southern pp 242–245

  • Fisher RA (1925) Theory of statistical estimation. Proc Camb Philos Soc 22: 700–725

    Article  Google Scholar 

  • Friman O, Luth T, Volosyak I, Graser A (2007) Spelling with steady-state visual evoked potentials. 3rd International IEEE/EMBS conference on neural engineering, pp 354–357

  • Gersch W (1970) Spectral analysis of EEGs by autoregressive decomposition of time series. Math Biosci 7: 205–222

    Article  Google Scholar 

  • Gevins AS (1984) Analysis of electromagnetic signals of the human brain: Milestones, obstacles, and goals. IEEE Trans Biomed Eng 31: 833–850

    Article  PubMed  CAS  Google Scholar 

  • Heckenlively JR, Arden GB (1991) Principles and practice of clinical electrophysiology of vision. Mosby, St Louis

    Google Scholar 

  • Kay SM (1988) Modern spectral estimation. Prentice-Hall, Englewood Cliffs

    Google Scholar 

  • Lehmann EL (1991) Testing statistical hypothesis. Statistical/probability series. Wadsworth and Brooks/Cole, Pacific Grove

  • Lorden G (1971) Procedures for reacting to a change in distribution. Ann Math Stat 42: 1897–1908

    Article  Google Scholar 

  • McGillem CD, Aunon JI, Yu KB (1985) Signal and noise in evoked potentials. IEEE Trans Biomed Eng 32: 1012–1016

    Article  PubMed  CAS  Google Scholar 

  • Middendorf M, McMillan G, Calhoun G, Jones KS (2000) Brain–computer interfaces based on the steady-state visual-evoked response. IEEE Trans Neural Syst Rehabil Eng 8: 217–229

    Google Scholar 

  • Nuwer M, Daube J, Fischer C, Schramm J, Yingling C (1993) Neuromonitoring during Surgery, Report of an IFCN Committee. Electroencephalogr Clin Neurophysiol 87(5): 273–276

    Google Scholar 

  • Nuwer MR, Dawson EG, Carlson LG, Kanim L, Sherman JE (1995) Somatosensory evoked potential monitoring reduces neurologic deficits after scoliosis surgery: Results of a large multicenter survey. Electroencephalogr Clin Neurophysiol 96: 6–11

    Article  PubMed  CAS  Google Scholar 

  • Orfanidis SJ (1996) Optimum signal processing. An introduction. 2. Prentice-Hall, Englewood Cliffs

    Google Scholar 

  • Pratt H, Matrin WH, Bleich N, Zaaroor M, Shacham SE (1994) High intensity, goggle-mounted flash stimulator for short-latency visual evoked potentials. Electroencephalogr Clin Neurophysiol 92: 469–472

    Article  PubMed  CAS  Google Scholar 

  • Robey FC, Fuhrmann DR, Nitzberg R, Kelly EJ (1992) A CFAR adaptive matched filter detector. IEEE Trans Aerosp Electron Syst 28: 208–216

    Article  Google Scholar 

  • Schacham SE, Pratt H (1985) Detection and measurement of steady-state evoked potentials using a lock-in amplifier. J Neuroserg 62: 935–938

    Article  CAS  Google Scholar 

  • Scofield JH (1994) Frequency-domain description of a lock-in amplifier. Am J Phys 62((2): 129–133

    Article  Google Scholar 

  • Wiedemayer H, Fauser B, Sandalcioglu IE, Armbruster W, Stolke D (2004) Observations on intraoperative monitoring of visual pathways using steady-state visual evoked potentials. Eur J Anaesthesiol 21: 429–433

    PubMed  CAS  Google Scholar 

  • Zaaroor M, Pratt H, Feinsod M, Shacham SE (1993) Real time monitoring of steady-state visual evoked potentials. Isr J Med Sci 29(1): 17–22

    PubMed  CAS  Google Scholar 

  • Zetterberg LH (1969) Estimation of parameters for a linear difference equation wih applications to EEG analysis. Math Biosci 5: 227–275

    Article  Google Scholar 

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Correspondence to Gideon Nave.

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Hillel Pratt and Menashe Zaaroor contributed equally to this study.

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Nave, G., Eldar, Y.C., Inbar, G. et al. Real-time change detection of steady-state evoked potentials. Biol Cybern 107, 49–59 (2013). https://doi.org/10.1007/s00422-012-0523-5

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  • DOI: https://doi.org/10.1007/s00422-012-0523-5

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