NDLI: Dynamic feature extraction of epileptic EEG using recurrence quantification analysis

Content Provider	IEEE Xplore Digital Library
Author	Lanlan Chen Junzhong Zou Jian Zhang
Copyright Year	2012
Description	Author affiliation: Department of Automation, East China University of Science and Technology, Shanghai, 200237, China (Lanlan Chen; Junzhong Zou; Jian Zhang)
Abstract	Detecting the reliable transition point embedded in the electroencephalograms (EEGs) is a challenge in the field of epileptic research. In this research, a recurrence quantification analysis (RQA) is proposed to help medical doctors to reveal dynamical characteristics in EEGs of patients suffering from epilepsy. In contrast with traditional chaos methods, the merits of RQA method is that it can measure the complexity of a short and non-stationary signal without any assumptions such as linear, stationary and noiseless noise. In this study, EEGs with generalized epilepsy were collected in Epilepsy Center of Renji Hospital. The test results show that three RQA measurements, i.e. recurrence rate, determinism and entropy can track the complexity changes of brain electrical activity. RQA variables show a large fluctuation in pre-ictal stage, which reflects a transitional state leading to seizure activity. On the contrary, RQA variables fluctuate in relatively small bounds in ictal stage, which is due to organized and self-sustained rhythmic discharge. Therefore, RQA could be a promising approach in prediction and diagnosis for epileptic seizures.
Starting Page	5019
Ending Page	5022
File Size	176163
Page Count	4
File Format	PDF
ISBN	9781467313971
e-ISBN	9781467313988
DOI	10.1109/WCICA.2012.6359429
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-06
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electroencephalography Epilepsy Complexity theory Standards Medical diagnostic imaging Noise measurement Dynamic Feature Epileptic Seizure EEG Recurrence quantification analysis (RQA)
Content Type	Text
Resource Type	Article

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