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Alzheimer's disease (AD) is the most common neurodegenerative disorder. Although a definite diagnosis is only possible by necropsy, a differential diagnosis with other types of dementia and with major depression should be attempted. The aim of this study was to analyse the electroencephalogram (EEG) background activity of AD patients to test the hypothesis(More)
We analyzed time series generated by 20 schizophrenic patients and 20 sex- and age-matched control subjects using three nonlinear methods of time series analysis as test statistics: central tendency measure (CTM) from the scatter plots of first differences of data, approximate entropy (ApEn), and Lempel-Ziv (LZ) complexity. We divided our data into a(More)
We present an automatic image processing algorithm to detect hard exudates. Automatic detection of hard exudates from retinal images is an important problem since hard exudates are associated with diabetic retinopathy and have been found to be one of the most prevalent earliest signs of retinopathy. The algorithm is based on Fisher's linear discriminant(More)
OBJECTIVE The aim of this study was to analyse the regularity of the EEG background activity of Alzheimer's disease (AD) patients to test the hypothesis that the irregularity of the AD patients' EEG is lower than that of age-matched controls. METHODS We recorded the EEG from 19 scalp electrodes in 10 AD patients and 8 age-matched controls and estimated(More)
OBJECTIVE In this study, we applied a novel procedure to calculate the mean frequency from the Magnetoencephalography (MEG) signals of 22 patients with Alzheimer's Disease (AD), 22 patients with mild cognitive impairment (MCI), and 21 healthy controls. A significant mean frequency decrease was expected in pathological groups. MCI subjects are expected to(More)
Alzheimer's disease (AD) is an irreversible brain disorder which represents the most common form of dementia in western countries. An early and accurate diagnosis of AD would enable to develop new strategies for managing the disease; however, nowadays there is no single test that can accurately predict the development of AD. In this sense, only a few(More)
In this study, we explored the ability of several spectral based measures to summarize the information of the power spectral density (PSD) function from spontaneous magnetoencephalographic (MEG) activity in Alzheimer's disease (AD). The MEGs of 20 AD patients and 21 elderly controls were recorded with eyes closed at rest during 5 min from 148 channels. Five(More)
The aim of the present study is to analyze the magnetoencephalogram (MEG) background activity from patients with Alzheimer's disease (AD) and elderly control subjects. MEG recordings from 20 AD patients and 21 controls were analyzed by means of two spectral [median frequency (MF) and spectral entropy (SpecEn)] and two nonlinear parameters [approximate(More)
Alzheimer's disease (AD) is the most common form of dementia. Ageing is the greatest known risk factor for this disorder. Therefore, the prevalence of AD is expected to increase in western countries due to the rise in life expectancy. Nowadays, a low diagnosis accuracy is reached, but an early and accurate identification of AD should be attempted. In this(More)
Quantitative magnetoencephalography (qMEG) was used to investigate differences in the 2 to 60 Hz spectral power, between Alzheimer disease (AD) patients and control subjects. Twenty-two AD patients and 21 age-matched control subjects participated in this study. MEG signal analysis comprised the division of the entire 2 to 60 Hz spectrum in 2 Hz-width(More)