ORCID

https://orcid.org/0009-0007-6180-0342

Keywords

electroencephalogram, complexity, nonlinear dynamics, sample entropy, Higuchi's fractal dimension, multiple sclerosis

Abstract

The application of nonlinear analysis in studying electroencephalography (EEG) signals has been increasingly applied to patients with neurological disorders, such as multiple sclerosis (MS). Various nonlinear analysis methods have been employed to investigate MS, offering unique insights into understanding, diagnosing, and treating the condition. This study utilized two nonlinear analyses, sample entropy (SampEn) and Higuchi’s fractal dimension (HFD), to explore the effects of Interferon-β (IFN-β) and dimethyl fumarate (DMF) on patients with MS. Data were collected from 175 participants at Jagiellonian University in Krakow, Poland, across three groups: IFN-β (n = 39), DMF (n = 53), and healthy controls (n = 83) during a resting state for six minutes. Participants were asked to keep their eyes open for the first three minutes and closed for the last three minutes without any stimuli. Both treatment groups underwent two rounds of data collection, with the second round occurring a year later. The results indicated that both treatment groups displayed more complex EEG signals than the control group, with SampEn showing greater sensitivity to the effects of the treatment than HFD. However, HFD was more responsive to temporal changes, especially in the DMF group. These findings highlight the effectiveness of nonlinear analysis methods, and while these results further our understanding of the complexities associated with MS, they also can be valuable for treatment development.

Completion Date

2024

Semester

Fall

Committee Chair

Karwowski, Waldemar

Degree

Doctor of Philosophy (Ph.D.)

College

College of Engineering and Computer Science

Department

Department of Industrial Engineering and Management Systems

Format

PDF

Identifier

DP0029699

Document Type

Thesis

Campus Location

Orlando (Main) Campus

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