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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http://dx.doi.org/10.1016/j.medengphy.2008.06.010 | DOI Listing |
Cogn Neurodyn
December 2025
Department of Electrical and Electronics Engineering, Jazan, 45142 Jazan Saudi Arabia.
Alzheimer's disease (AD) is a chronic disability that occurs due to the loss of neurons. The traditional methods to detect AD involve questionnaires and expensive neuro-imaging tests, which are time-consuming, subjective, and inconvenient to the target population. To overcome these limitations, Electroencephalogram (EEG) based methods have been developed to classify AD patients from normal controlled (NC) and mild cognitive impairment (MCI) subjects.
View Article and Find Full Text PDFPharmaceutics
December 2024
Department of Physico-Chemistry, Faculty of Pharmacy, "Grigore T. Popa" University of Medicine and Pharmacy, 16 Universității Street, 700115 Iasi, Romania.
Diabetes is a growing global health crisis that requires effective therapeutic strategies to optimize treatment outcomes. This study aims to address this challenge by developing and characterizing extended-release polymeric matrix tablets containing metformin hydrochloride (M-HCl), a first-line treatment for type 2 diabetes, and honokiol (HNK), a bioactive compound with potential therapeutic benefits. The objective is to enhance glycemic control and overall therapeutic outcomes through an innovative dual-drug delivery system.
View Article and Find Full Text PDFSensors (Basel)
November 2024
Department of Health Technologies, Tallinn University of Technology, 19086 Tallinn, Estonia.
This study aims to investigate the association between the natural level of blood biomarkers and electroencephalographic (EEG) markers. Resting EEG theta, alpha (ABP), beta, and gamma frequency band powers were selected as linear EEG markers indicating the level of EEG power, and Higuchi's fractal dimension (HFD) as a nonlinear EEG complexity marker reflecting brain temporal dynamics. The impact of seven different blood biomarkers, i.
View Article and Find Full Text PDFClin Neurophysiol
December 2024
Dipartimento di Neuroscienze, Università degli Studi di Padova, Italy; Padova Neuroscience Center, Università degli Studi di Padova, Italy. Electronic address:
Objective: Complex visual hallucinations (VH) are a core feature of dementia with Lewy bodies (DLB), though they may not occur in all patients. Power spectral density (PSD) analysis of resting-state EEG (rs-EEG) shows associations between some frequency bands (e.g.
View Article and Find Full Text PDFFront Neuroinform
July 2024
Statistics Program, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.
Topological data analysis (TDA) is increasingly recognized as a promising tool in the field of neuroscience, unveiling the underlying topological patterns within brain signals. However, most TDA related methods treat brain signals as if they were static, i.e.
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