Seizure detection method based on fractal dimension and gradient boosting

Epilepsy and Behavior

Volumn 43, Issue , 2015, Pages 30-38

  Zhang, Yanli ^a,b   Zhou, Weidong ^a   Yuan, Shasha ^a   Yuan, Qi ^a  

^a SHANDONG UNIVERSITY   (China)

^b SHANDONG INSTITUTE OF BUSINESS AND TECHNOLOGY   (China)

Author keywords

EEG; Fractal dimension; Gradient boosting; Seizure detection

Indexed keywords

ALGORITHM; ARTICLE; CLINICAL ARTICLE; DIAGNOSTIC TEST ACCURACY STUDY; ELECTROENCEPHALOGRAPHY; EVALUATION STUDY; FRACTAL ANALYSIS; HUMAN; K NEAREST NEIGHBOR; PERFORMANCE; PROBABILITY; RECOGNITION; SEIZURE; SENSITIVITY AND SPECIFICITY; DEVICES; LABORATORY DIAGNOSIS; PATIENT CARE; REPRODUCIBILITY; SEIZURES; STATISTICAL ANALYSIS; STATISTICS AND NUMERICAL DATA;

ALGORITHMS; DATA INTERPRETATION, STATISTICAL; ELECTROENCEPHALOGRAPHY; FALSE POSITIVE REACTIONS; FRACTALS; HUMANS; PATIENT-CENTERED CARE; REPRODUCIBILITY OF RESULTS; SEIZURES;

EID: 84919917551     PISSN: 15255050     EISSN: 15255069     Source Type: Journal    
DOI: 10.1016/j.yebeh.2014.11.025     Document Type: Article

References (45)

1. Shoeb A., Edwards H., Connolly J., Bourgeois B., Treves S.T., Guttag J. Patient-specific seizure onset detection. Epilepsy Behav 2004, 5(4):483-498.
2. Lagerlund T.D., Cascino G.D., Cicora K.M., Sharbrough F.W. Long-term electroencephalographic monitoring for diagnosis and management of seizures. Mayo Clin Proc 1996, 71(10):1000-1006.
3. Gotman J. Automatic recognition of epileptic seizures in the EEG. Electroencephalogr Clin Neurophysiol 1982, 54(5):530-540.
4. Gotman J. Automatic seizure detection: improvements and evaluation. Electroencephalogr Clin Neurophysiol 1990, 76(4):317-324.
5. Qu H., Gotman J. Improvement in seizure detection performance by automatic adaptation to the EEG of each patient. Electroencephalogr Clin Neurophysiol 1993, 86(2):79-87.
6. Qu H., Gotman J. A patient-specific algorithm for the detection of seizure onset in long-term EEG monitoring: possible use as a warning device. IEEE Trans Biomed Eng 1997, 44(2):115-122.
7. Grewal S., Gotman J. An automatic warning system for epileptic seizures recorded on intracerebral EEGs. Clin Neurophysiol 2005, 116(10):2460-2472.
8. Gabor A.J., Leach R.R., Dowla F.U. Automated seizure detection using a self-organizing neural network. Electroencephalogr Clin Neurophysiol 1996, 99(3):257-266.
9. Wilson S.B. A neural network method for automatic and incremental learning applied to patient-dependent seizure detection. Clin Neurophysiol 2005, 116(8):1785-1795.
10. Srinivasan V., Eswaran C., Sriraam N. Approximate entropy-based epileptic EEG detection using artificial neural networks. IEEE Trans Inf Technol Biomed 2007, 11(3):288-295.
11. Gardner A.B., Krieger A.M., Vachtsevanos G.J., Litt B. One-class novelty detection for seizure analysis from intracranial EEG. J Mach Learn Res 2006, 7:1025-1044.
12. Meier R., Dittrich H., Schulze-Bonhage A., Aertsen A. Detecting epileptic seizures in long-term human EEG: a new approach to automatic online and real-time detection and classification of polymorphic seizure patterns. J Clin Neurophysiol 2008, 25(3):119-131.
13. Temko A., Thomas E., Marnane W., Lightbody G., Boylan G. EEG-based neonatal seizure detection with support vector machines. Clin Neurophysiol 2011, 122(3):464-473.
14. Altunaya S., Telatarb Z., Erogulc O. Epileptic EEG detection using the linear prediction error energy. Expert Syst Appl 2010, 37(8):5661-5665.
15. Mohamed B.V., Farooq O., Khan Y.U. Automatic seizure detection using higher order moments. International conference on recent trends in information, telecommunication and computing 2010, 159-163.
16. Faust O., Acharya U.R., Min L.C., Sputh B.H. Automatic identification of epileptic and background EEG signals using frequency domain parameters. Int J Neural Syst 2010, 20(2):159-176.
17. Ayoubian L., Lacoma H., Gotman J. Automatic seizure detection in SEEG using high frequency activities in wavelet domain. Med Eng Phys 2013, 35(3):319-328.
18. Conradsen I., Beniczky S., Wolf P., Kjaer T.W., Sams T., Sorensen H.B. Automatic multi-modal intelligent seizure acquisition (MISA) system for detection of motor seizures from electromyographic data and motion data. Comput Methods Programs Biomed 2012, 107(2):97-110.
19. Yuan S., Zhou W., Yuan Q., Zhang Y., Meng Q. Automatic seizure detection using diffusion distance and BLDA in intracranial EEG. Epilepsy Behav 2014, 31:339-345.
20. Martis R.J., Acharya U.R., Tan J.H., Petznick A., Yanti R., Chua C.K., et al. Application of empirical mode decomposition (emd) for automated detection of epilepsy using EEG signals. Int J Neural Syst 2012, 22(6):1250027.
21. Guler N.F., Ubey E.D., Guler I. Recurrent neural network employing Lyapunov exponents for EEG signals classification. Expert Syst Appl 2005, 29(3):506-514.
22. Ghosh-Dastidar S., Adeli H., Dadmehr N. Mixed-band wavelet-chaos-neural network methodology for epilepsy and epileptic seizure detection. IEEE Trans Biomed Eng 2007, 54(9):1545-1551.
23. Acharya U.R., Molinari F., Sree S.V., Chattopadhyay S., Ng Kwan-Hoong, Suri J.S. Automated diagnosis of epileptic EEG using entropies. Biomed Signal Process 2012, 7(4):401-408.
24. Kannathal N., Choo M.L., Acharya U.R., Sadasivan P.K. Entropies for detection of epilepsy in EEG. Comput Methods Programs Biomed 2005, 80(3):187-194.
25. Acharya U.R., Sree S.V., Swapna G., Martis R.J., Suri J.S. Automated EEG analysis of epilepsy: a review. Knowl-Based Syst 2013, 45:147-165.
26. Theiler J. Estimating fractal dimension. J Opt Soc Am A 1990, 7(6):1055-1073.
27. Termonia Y., Alexandrowicz Z. Fractal dimension of strange attractors from radius versus size of arbitrary clusters. Phys Rev Lett 1983, 51:1265-1268.
28. Asvestas P., Matsopoulos G.K., Nikita K.S. Estimation of fractal dimension of images using a fixed mass approach. Pattern Recogn Lett 1999, 20(3):347-354.
29. Polychronaki G.E., Ktonas P.Y., Gatzonis S., Siatouni A., Asvestas P.A., Tsekou H., et al. Comparison of fractal dimension estimation algorithms for epileptic seizure onset detection. J Neural Eng 2010, 7(4):046007.
30. Jin X.C., Ong S.H., Jayasooriah A practical method for estimating fractal dimension. Pattern Recogn Lett 1995, 16(5):457-464.
31. Katz M.J. Fractals and the analysis of waveforms. Comput Biol Med 1988, 18(3):145-156.
32. Higuchi T. Approach to an irregular time series on the basis of the fractal theory. Physica D 1988, 31(2):277-283.
33. Freund Y., Schapire R. A decision-theoretic generalization of on-line learning and an application to boosting. J Comput Syst Sci 1997, 55(1):119-139.
34. Friedman J.H. Greedy function approximation: a gradient boosting machine. Ann Stat 2001, 29:1189-1232.
35. Lawrence R., Bunn A., Powell S., Zambon M. Classification of remotely sensed imagery using stochastic gradient boosting as a refinement of classification tree analysis. Remote Sens Environ 2004, 90(3):331-336.
36. Hoffmann U., Garcia G., Vesin J.M., Diserens K., Ebrahimi T. A boosting approach to P300 detection with application to brain-computer interfaces. Conference Proceedings of the 2nd International IEEE EMBS Conference on Neural Engineering 2005, 97-100.
37. Schelter B., Winterhalder M., Maiwald T., Brandt A., Schad A., Timmer J., et al. Do false predictions of seizures depend on the state of vigilance? A report from two seizure-prediction methods and proposed remedies. Epilepsia 2006, 47(12):2058-2070.
38. Aarabi A., Fazel-Rezai R., Aghakhani Y. A fuzzy rule-based system for epileptic seizure detection in intracranial EEG. Clin Neurophysiol 2009, 120(9):1648-1657.
39. Maiwald T., Winterhalder M., Aschenbrenner-Scheibe R., Voss H.U., Schulze-Bonhage A., Timmer J. Comparison of three nonlinear seizure prediction methods by means of the seizure prediction characteristic. Physica D 2004, 194:357-368.
40. Temko A., Thomas E., Marnane W., Lightbody G., Boylan G.B. Performance assessment for EEG-based neonatal seizure detectors. Clin Neurophysiol 2011, 122(3):474-482.
41. Zhang Y., Zhou W., Yuan Q., Wu Q. A low computation cost method for seizure prediction. Epilepsy Res 2014, 108(8):1357-1366.
42. Yuan Q., Zhou W., Liu Y., Wang J. Epileptic seizure detection with linear and nonlinear features. Epilepsy Behav 2012, 24(4):415-421.
43. Esteller R., Echauz J., Tcheng T., Litt B., Pless B. Line length: an efficient feature for seizure onset detection. Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2001, 2:1707-1710.
44. Chua E.C., Patel K., Fitzsimons M., Bleakley C.J. Improved patient specific seizure detection during pre-surgical evaluation. Clin Neurophysiol 2011, 122(4):672-679.
45. Raghunathan S., Jaitli A., Irazoqui P.P. Multistage seizure detection techniques optimized for low-power hardware platforms. Epilepsy Behav 2011, 22:S61-S68.