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Cognitive Neurodynamics

, Volume 12, Issue 2, pp 183–199 | Cite as

Analysis of long range dependence in the EEG signals of Alzheimer patients

  • T. Nimmy John
  • Subha D. Puthankattil
  • Ramshekhar Menon
Research Article

Abstract

Alzheimer’s disease (AD), a cognitive disability is analysed using a long range dependence parameter, hurst exponent (HE), calculated based on the time domain analysis of the measured electrical activity of brain. The electroencephalogram (EEG) signals of controls and mild cognitive impairment (MCI)-AD patients are evaluated under normal resting and mental arithmetic conditions. Simultaneous low pass filtering and total variation denoising algorithm is employed for preprocessing. Larger values of HE observed in the right hemisphere of the brain for AD patients indicated a decrease in irregularity of the EEG signal under cognitive task conditions. Correlations between HE and the neuropsychological indices are analysed using bivariate correlation analysis. The observed reduction in the values of Auto mutual information and cross mutual information in the local antero-frontal and distant regions in the brain hemisphere indicates the loss of information transmission in MCI-AD patients.

Keywords

Alzheimer’s disease EEG Multi-resolution decomposition Hurst exponent Auto mutual information Cross mutual information 

Notes

Acknowledgements

The authors wish to acknowledge Dr. P.S. Mathuranath for his valuable advice. This research is carried out with the funding received from Science and Engineering Research Board (DST-SERB- No. SR/FTP/ETA-102/2010), Department of Science and Technology, Government of India.

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© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Electrical EngineeringNational Institute of Technology CalicutKozhikodeIndia
  2. 2.Department of NeurologySree Chitra Tirunal Institute for Medical Sciences and TechnologyThiruvananthapuramIndia

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