Investigation of the noise effect on fractal dimension of EEG in schizophrenia patients using wavelet and SSA-based approaches

Akar S. A., Kara S., LATİFOĞLU F., Bilgic V.

BIOMEDICAL SIGNAL PROCESSING AND CONTROL, vol.18, pp.42-48, 2015 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 18
  • Publication Date: 2015
  • Doi Number: 10.1016/j.bspc.2014.11.004
  • Journal Name: BIOMEDICAL SIGNAL PROCESSING AND CONTROL
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.42-48
  • Keywords: EEG, Katz's fractal dimension, Noise removal, Wavelet decomposition, Singular spectrum analysis, Chronic schizophrenia, ALZHEIMERS-DISEASE, COMPLEXITY, NONLINEARITY, TRANSFORM, DEFICITS
  • Erciyes University Affiliated: Yes

Abstract

Objectives: Complexity measures have been enormously used in schizophrenia patients to estimate brain dynamics. However, the conflicting results in terms of both increased and reduced complexity values have been reported in these studies depending on the patients' clinical status or symptom severity or medication and age status. The objective of this study is to investigate the nonlinear brain dynamics of chronic, medicated schizophrenia patients and healthy control subjects using Katz's fractal dimension (FD). Moreover, in order to determine noise effect on complexity of EEG data, a noise elimination method based on wavelet and singular spectrum analysis (SSA) were assessed.