New approach to epileptic diagnosis using visibility graph of high-frequency signal

Clinical EEG and Neuroscience

Volumn 44, Issue 2, 2013, Pages 150-156

  Tang, Xiaoying ^a   Xia, Li ^a   Liao, Yezi ^a   Liu, Weifeng ^a   Peng, Yuhua ^a   Gao, Tianxin ^a   Zeng, Yanjun ^b  

^a BEIJING INSTITUTE OF TECHNOLOGY   (China)

^b BEIJING UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

Complexity; ECoG; Epilepsy; Visual graph

Indexed keywords

ALGORITHM; ARTICLE; CASE REPORT; ELECTROCORTICOGRAPHY; ELECTRODE; ENTROPY; EPILEPSY; HUMAN; PRIORITY JOURNAL; TIME SERIES ANALYSIS; VISIBILITY; BRAIN MAPPING; COMPLEXITY; DIFFERENTIAL DIAGNOSIS; ELECTROENCEPHALOGRAPHY; METHODOLOGY; PATHOPHYSIOLOGY; SIGNAL PROCESSING; VISUAL GRAPH;

COMPLEXITY; ECOG; EPILEPSY; VISUAL GRAPH;

ALGORITHMS; BRAIN MAPPING; DIAGNOSIS, DIFFERENTIAL; ELECTROENCEPHALOGRAPHY; EPILEPSY; HUMANS; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 84883021594     PISSN: 15500594     EISSN: 21695202     Source Type: Journal    
DOI: 10.1177/1550059412464449     Document Type: Article

References (17)

1. Smith SJ. EEG in the diagnosis, classification, and management of patients with epilepsy. J Neurol Neurosurg Psychiatry. 2005; 76(suppl 2):ii2-ii7.
2. Fisher RS, Webber WR, Lesser RP, Arroyo S, Uematsu S. High-frequency EEG activity at the start of seizures. J Clin Neurophysiol. 1992;9(3):441-448.
3. Jacobs J, LeVan P, Chander R, Hall J, Dubeau F, Gotman J. Interictal high-frequency oscillations (80-500 Hz) are an indicator of seizure onset areas independent of spikes in the human epileptic brain. Epilepsia. 2008;49(11):1893-1907.
4. Ochi A, Otsubo H, Donner EJ, et al Dynamic changes of ictal high-frequency oscillations in neocortical epilepsy: using multiple band frequency analysis. Epilepsia. 2007;48(2):286-296.
5. Klonowski W. Complexity measures of brain electrophysiological activity in consciousness, under anesthesia, during epileptic seizure, and in physiological sleep. J Psychophysiol. 2010;24:131-135.
6. Protzner AB, Valiante TA, Kovacevic N, McCormick C, McAndrews MP. Hippocampal signal complexity in mesial temporal lobe epilepsy: a noisy brain is a healthy brain. Arch Ital Biol. 2010;148(3):289-297.
7. Zandi AS, Dumont GA, Javidan M, Tafreshi R. An entropy-based approach to predict seizures in temporal lobe epilepsy using scalp EEG. Conf Proc IEEE Eng Med Biol Soc. 2009;2009:228-231.
8. Kumar SP. Entropies based detection of epileptic seizures with artificial neural network classifiers. Expert Syst Appl. 2010;37: 3284-3291.
9. Cuo L, Rivero D, Pazos A. Epileptic seizure detection using multiwavelet transform based approximate entropy and artificial neural networks. J Neurosci Methods. 2010;193(1):156-163.
10. Lacasa L, Luque B, Ballesteros F, Luque J, Nuño JC. From time series to complex networks: the visibility graph. Proc Natl Acad Sci U S A. 2008;105(13):4972-4975.
11. Lacasa L. The visibility graph: a new method for estimating the Hurst exponent of fractional Brownian motion. Europhys Lett. 2009;86(3):30001-30004.
12. Ahmadlou M, Adeli H, Adeli A. New diagnostic EEG markers of the Alzheimer's disease using visibility graph. J Neural Transm. 2010;117(9):1099-1109.
13. Kim J, Wilhelm T. What is a complex graph? Physica A Stat Mech Appl. 2008;387(11):2637-2652.
14. Weixing H. The analysis of the sleep EEG using sample entropy. Control Automation. 2007;1:216-217.
15. Richman JS. Sample entropy statistics and testing for order in complex physiological signals. Commun Stat Theory Methods. 2007;36:1005-1019.
16. Abásolo D, James CJ, Hornero R. Non-linear analysis of intracranial electroencephalogram recordings with approximate entropy and Lempel-Ziv complexity for epileptic seizure detection. Conf Proc IEEE Eng Med Biol Soc. 2007;2007:1953-1956.
17. Limniotis K. On the nonlinear complexity and Lempel-Ziv complexity of finite length sequences. IEEE Trans Inf Theory. 2007; 53:4293-4302.