EEG Analysis in Structural Focal Epilepsy Using the Methods of Nonlinear Dynamics (Lyapunov Exponents, Lempel-Ziv Complexity, and Multiscale Entropy)

Autor: Tatiana Yu Yaroshenko, Antonina Yu. Karas, Maxim V. Zhigalov, Anton V. Krysko, V. Dobriyan, Nikolai M Yakovlev, Irina V Papkova, Nikolai P Erofeev, I. E. Kutepov, O. A. Saltykova, T. V. Yakovleva, Vadim A. Krysko
Rok vydání: 2019
Předmět:
Data Analysis
Technology
Article Subject
Computer science
Science
Physics::Medical Physics
02 engineering and technology
Lyapunov exponent
Electroencephalography
General Biochemistry
Genetics and Molecular Biology
Multiscale entropy
03 medical and health sciences
Epilepsy
symbols.namesake
0302 clinical medicine
0202 electrical engineering
electronic engineering
information engineering
medicine
Humans
General Environmental Science
Signal processing
medicine.diagnostic_test
Series (mathematics)
Quantitative Biology::Neurons and Cognition
Spectrum (functional analysis)
Signal Processing
Computer-Assisted
General Medicine
medicine.disease
Magnetic Resonance Imaging
Nonlinear system
Nonlinear Dynamics
symbols
Medicine
020201 artificial intelligence & image processing
Epilepsies
Partial
Algorithm
030217 neurology & neurosurgery
Algorithms
Research Article
Zdroj: The Scientific World Journal
The Scientific World Journal, Vol 2020 (2020)
ISSN: 1537-744X
Popis: This paper analyzes a case with the patient having focal structural epilepsy by processing electroencephalogram (EEG) fragments containing the “sharp wave” pattern of brain activity. EEG signals were recorded using 21 channels. Based on the fact that EEG signals are time series, an approach has been developed for their analysis using nonlinear dynamics tools: calculating the Lyapunov exponent’s spectrum, multiscale entropy, and Lempel–Ziv complexity. The calculation of the first Lyapunov exponent is carried out by three methods: Wolf, Rosenstein, and Sano–Sawada, to obtain reliable results. The seven Lyapunov exponent spectra are calculated by the Sano–Sawada method. For the observed patient, studies showed that with medical treatment, his condition did not improve, and as a result, it was recommended to switch from conservative treatment to surgical. The obtained results of the patient’s EEG study using the indicated nonlinear dynamics methods are in good agreement with the medical report and MRI data. The approach developed for the analysis of EEG signals by nonlinear dynamics methods can be applied for early detection of structural changes.
Databáze: OpenAIRE
Externí odkaz: