Literature DB >> 18676171

Use of the Higuchi's fractal dimension for the analysis of MEG recordings from Alzheimer's disease patients.

Carlos Gómez1, Angela Mediavilla, Roberto Hornero, Daniel Abásolo, Alberto Fernández.   

Abstract

Alzheimer's disease (AD) is an irreversible brain disorder of unknown aetiology that gradually destroys brain cells and represents the most prevalent form of dementia in western countries. The main aim of this study was to analyse the magnetoencephalogram (MEG) background activity from 20 AD patients and 21 elderly control subjects using Higuchi's fractal dimension (HFD). This non-linear measure can be used to estimate the dimensional complexity of biomedical time series. Before the analysis with HFD, the stationarity and the non-linear structure of the signals were proved. Our results showed that MEG signals from AD patients had lower HFD values than control subjects' recordings. We found significant differences between both groups at 71 of the 148 MEG channels (p<0.01; Student's t-test with Bonferroni's correction). Additionally, five brain regions (anterior, central, left lateral, posterior and right lateral) were analysed by means of receiver operating characteristic curves, using a leave-one-out cross-validation procedure. The highest accuracy (87.8%) was achieved when the mean HFD over all channels was analysed. To sum up, our results suggest that spontaneous MEG rhythms are less complex in AD patients than in healthy control subjects, hence indicating an abnormal type of dynamics in AD.

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Year:  2008        PMID: 18676171     DOI: 10.1016/j.medengphy.2008.06.010

Source DB:  PubMed          Journal:  Med Eng Phys        ISSN: 1350-4533            Impact factor:   2.242


  20 in total

1.  Fractal dimension values of cerebral and cerebellar activity in rats loaded with aluminium.

Authors:  Goran Kekovic; Milka Culic; Ljiljana Martac; Gordana Stojadinovic; Ivan Capo; Dusan Lalosevic; Slobodan Sekulic
Journal:  Med Biol Eng Comput       Date:  2010-04-28       Impact factor: 2.602

2.  Correlating brain blood oxygenation level dependent (BOLD) fractal dimension mapping with magnetic resonance spectroscopy (MRS) in Alzheimer's disease.

Authors:  Mohammed A Warsi; William Molloy; Michael D Noseworthy
Journal:  MAGMA       Date:  2012-03-24       Impact factor: 2.310

3.  New diagnostic EEG markers of the Alzheimer's disease using visibility graph.

Authors:  Mehran Ahmadlou; Hojjat Adeli; Anahita Adeli
Journal:  J Neural Transm (Vienna)       Date:  2010-08-17       Impact factor: 3.575

4.  Functional Connectivity and Complexity in the Phenomenological Model of Mild Cognitive-Impaired Alzheimer's Disease.

Authors:  Surya Das; Subha D Puthankattil
Journal:  Front Comput Neurosci       Date:  2022-06-06       Impact factor: 3.387

5.  Discrimination of stroke-related mild cognitive impairment and vascular dementia using EEG signal analysis.

Authors:  Noor Kamal Al-Qazzaz; Sawal Hamid Bin Mohd Ali; Siti Anom Ahmad; Mohd Shabiul Islam; Javier Escudero
Journal:  Med Biol Eng Comput       Date:  2017-11-08       Impact factor: 2.602

6.  Heart rate variability analysis during central hypovolemia using wavelet transformation.

Authors:  Soo-Yeon Ji; Ashwin Belle; Kevin R Ward; Kathy L Ryan; Caroline A Rickards; Victor A Convertino; Kayvan Najarian
Journal:  J Clin Monit Comput       Date:  2013-02-01       Impact factor: 2.502

7.  Integration of 24 Feature Types to Accurately Detect and Predict Seizures Using Scalp EEG Signals.

Authors:  Yinda Zhang; Shuhan Yang; Yang Liu; Yexian Zhang; Bingfeng Han; Fengfeng Zhou
Journal:  Sensors (Basel)       Date:  2018-04-28       Impact factor: 3.576

8.  Entropy and Complexity Analyses in Alzheimer's Disease: An MEG Study.

Authors:  Carlos Gómez; Roberto Hornero
Journal:  Open Biomed Eng J       Date:  2010-10-10

9.  A new diagnostic vestibular evoked response.

Authors:  Zeinab A Dastgheib; Brian Lithgow; Brian Blakley; Zahra Moussavi
Journal:  J Otolaryngol Head Neck Surg       Date:  2015-04-11

10.  The Analysis of the Influence of Odorant's Complexity on Fractal Dynamics of Human Respiration.

Authors:  Hamidreza Namazi; Amin Akrami; Vladimir V Kulish
Journal:  Sci Rep       Date:  2016-05-31       Impact factor: 4.379

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