Standardized database development for EEG epileptiform transient detection: EEGnet scoring system and machine learning analysis

Journal of Neuroscience Methods

Volumn 212, Issue 2, 2013, Pages 308-316

  Halford, Jonathan J ^a   Schalkoff, Robert J ^b   Zhou, Jing ^b   Benbadis, Selim R ^c   Tatum, William O ^d   Turner, Robert P ^a   Sinha, Saurabh R ^e   Fountain, Nathan B ^f   Arain, Amir ^g   Pritchard, Paul B ^a   Kutluay, Ekrem ^a   Martz, Gabriel ^a   Edwards, Jonathan C ^a   Waters, Chad ^b   Dean, Brian C ^b  

^a MEDICAL UNIVERSITY OF SOUTH CAROLINA   (United States)

^b Clemson University   (United States)

^c UNIVERSITY OF SOUTH FLORIDA   (United States)

^d MAYO CLINIC   (United States)

^e DUKE UNIVERSITY MEDICAL CENTER   (United States)

^f UNIVERSITY OF VIRGINIA   (United States)

^g VANDERBILT UNIVERSITY MEDICAL CENTER   (United States)

Author keywords

Automated interpretation; Computerized interpretation; Electroencephalogram (EEG); Electroencephalography; Epileptiform transient; Spike detection

Indexed keywords

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; BAYESIAN LEARNING; COMPUTER PROGRAM; EEGNET SCORING SYSTEM; ELECTROENCEPHALOGRAPHY; EPILEPTIC DISCHARGE; MACHINE LEARNING; PRIORITY JOURNAL; SCORING SYSTEM; SENSITIVITY AND SPECIFICITY; WAVEFORM; WEB BROWSER;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; ELECTROENCEPHALOGRAPHY; EPILEPSY; HUMANS; SIGNAL PROCESSING, COMPUTER-ASSISTED; SOFTWARE;

EID: 84870769794     PISSN: 01650270     EISSN: 1872678X     Source Type: Journal    
DOI: 10.1016/j.jneumeth.2012.11.005     Document Type: Article

References (32)

1. Acir N., Oztura I., Kuntalp M., Baklan B., Guzeli C. Automatic detection of epileptiform events in EEG by a three-stage procedure based on artificial neural networks. IEEE Trans Biomed Eng 2005, 52:30-40.
2. Benbadis S.R. Errors in EEGs and the misdiagnosis of epilepsy: importance, causes, consequences, and proposed remedies. Epilepsy Behav 2007, 11:257-262.
3. Berdakh A., Don S.H. Epileptic seizures detection using continuous wavelet based artificial neural networks. ITNG'09 Proceedings of the 2009 Sixth International Conference on Information Technology: New Generations 2009, 1456-1461.
4. Castellaro C., Favaro G., Castellaro A., Casagrande A., Castellaro S., Puthenparampil D.V., et al. An artificial intelligence approach to classify and analyse EEG traces. Neurophysiol Clin 2002, 32:193-214.
5. De Lucia M., Fritschy J., Dayan P., Holder D.S. A novel method for automated classification of epileptiform activity in the human electroencephalogram based on independent component analysis. Med Biol Eng Comput 2008, 46:263272.
6. Delorme A., Makeig S. EEGLab: an open source toolbox for analysis of single-trial EEG dynamics. J Neurosci Methods 2004, 134:9-21.
7. Epstein C.M. Guideline 4: standards of practice in clinical electroencephalography. J Clin Neurophysiol 2006, 23:86-91.
8. Fountain N.B., Freeman J.M. EEG is an essential clinical tool: pro and con. Epilepsia 2006, 4:23-25.
9. Guler I., Ubeyli E.D. Adaptive neuro-fuzzy inference system for classification of EEG signals using wavelet coefficients. J Neurosci Methods 2005, 148:113-121.
10. Halford J.J. Computerized epileptiform transient detection in scalp EEG: obstacles to progress and the example of computerized ECG interpretation. Clin Neurophysiol 2009, 120:1909-1915.
11. Halford J.J. Response to spike detection algorithm performance and methods of acquiring expert opinion. Clin Neurophysiol 2010, 121:1968.
12. Halford J.J., Pressly W.B., Benbadis S.R., Tatum W.O., Turner R.P., Arain A., et al. Web-based collection of expert opinion on routine scalp EEG: software development and inter-rater reliability. J Clin Neurophysiol 2011, 28:174-178.
13. Hostetler W.E., Doller H.J., Homan R.W. Assessment of a computer program to detect epileptiform spikes. Electroencephalogr Clin Neurophysiol 1992, 83:1-11.
14. Indiradevi K.P., Elias E., Sathidevi P.S., Dinesh Nayak S., Radhakrishnan K. A multi-level wavelet approach for automatic detection of epileptic spikes in the electroencephalogram. Comput Biol Med 2008, 38:805-816.
15. Jahankhani P., Kodogiannis V., Revett K. EEG signal classification using wavelet feature extraction and neural networks. IEEE John Vincent Atanasoff 2006 International Symposium on Modern Computing JVA06 2006, 120-124.
16. Kalayci T., Ozdamar O. Wavelet preprocessing for automated neural network detection of EEG spikes. IEEE Eng Med Biol 1995, 14:160-166.
17. Kemp B., Värri A., Rosa A.C., Nielsen K.D., Gade J. A simple format for exchange of digitized polygraphic recordings. Electroencephalogr Clin Neurophysiol 1992, 82:391-393.
18. Losey T.E., Uber-Zak L. Time to first interictal epileptiform discharge in extended recording EEGs. J Clin Neurophysiol 2008, 25:1-4.
19. Mirzaei A., Ayatollahi A., Gifani P., Salehi L. EEG analysis based on wavelet-spectral entropy for epileptic seizures detection. Biomedical Engineering and Informatics (BMEI), 2010 3rd International Conference, vol. 2 2010, 878-882.
20. Modur P.N., Rigdon B. Diagnostic yeild of sequential routine EEG and extended outpatient video-EEG monitoring. Clin Neurophysiol 2008, 119:190-196.
21. Osorio I., Frei M.G., Giftakis J., Peters T., Ingram J., Turnbull M., et al. Performance reassessment of a real-time seizure-detection algorithm on long ECoG series. Epilepsia 2002, 43:1522-1535.
22. Osorio I., Frei M.G., Wilkinson S.B. Real-time automated detection and quantitative analysis of seizures and short-term prediction of clinical onset. Epilepsia 1998, 39:615-627.
23. Osorio I., Lyubushin A., Sornette D. Toward and probabilistic definition of seizures. Epilepsy Behav 2011, 22:S18-S28.
24. Reuber M., Fernandez G., Bauer J., Helmstaedter C., Elger C.E. Diagnostic delay in psychogenic non-epileptic seizures. Neurology 2002, 58:493-495.
25. Schalkoff R.J. Pattern recognition: statistical, syntactic and neural approaches 1992, John Wiley and Sons, New York.
26. Van Donselaar C.A., Schimsheimer R., Geerts A.T., Declerck A.C. Value of the electroencephalogram in adult patients with untreated idiopathic first seizure. Arch Neurol 1992, 49:231-237.
27. van Drongelen W. Signal processing for neuroscientists. Wavelet analysis: frequency domain properties 2007, Academic Press, London, pp. 265-278.
28. Ver Hoef L., Elgavish R., Knowlton R.C. Effect of detection parameters on automated electroencephalography spike detection sensitivity and false-positive rate. J Clin Neurophysiol 2010, 27:12-16.
29. Webber W.R.S., Litt B., Lesser R.P., Fisher R.S., Bankman I. Automatic EEG spike detection: what should the computer imitate. Electroencephalogr Clin Neurophysiol 1993, 87:364-373.
30. Wilson S.B. Conversation at Persyst Corporate Headquarters 2012.
31. Wilson S.B., Harner R.N., Duffy F.H., Tharp B.R., Nuwer M.R., Sperling M.R. Spike detection. I: correlation and reliability of human experts. Electroencephalogr Clin Neurophysiol 1996, 98:186-198.
32. Wilson S.B., Turner C.A., Emerson R.G., Scheuer M.L. Spike detection. II: automatic, perception-based detection and clustering. Clin Neurophysiol 1999, 110:404-411.