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Abstract
Dementia has become a global public health issue. The current study is focused on diagnosing dementia with Electro Encephalography (EEG). The detection of the advancement of the disease is carried out by detecting the abnormal behavior in EEG measurements. Assessment and evaluation of EEG abnormalities is conducted for all the subjects in order to detect dementia. EEG feature analysis, namely dominant frequency, dominant frequency variability, and frequency prevalence, is done for abnormal and normal subjects and the results are compared. For dementia with Lewy bodies, in 85% of the epochs, the dominant frequency is present in the delta range whereas for normal subjects it lies in the alpha range. The dominant frequency variability in 75% of the epochs is above 4Hz for dementia with Lewy bodies, and in normal subjects at 72% of the epochs, the dominant frequency variability is less than 2Hz. It is observed that these features are sufficient to diagnose dementia with Lewy bodies. The classification of Lewy body dementia is done by using a feed-forward artificial neural network wich proved to have a 94.4% classification accuracy. The classification with the proposed feed-forward neural network has better accuracy, sensitivity, and specificity than the already known methods.
Highlights
The term dementia refers to a syndrome that causes a decline in cognitive functions, mainly the person’s memory and intelligence, due to the death of brain cells
Dominant Frequency Range (DFR), the range of maximum and minimum value of ܨ, Dominant Frequency Variability (DFV), the variation of the dominant frequency, i.e. the difference between the maximum and minimum value of ܨ, Frequency Prevalence (FP) which indicates the existence of a frequency ܨ in alpha, theta, or delta range were evaluated
Mean Dominant Frequency (MDF) is present in the delta range in all the analyzed subjects
Summary
The term dementia refers to a syndrome that causes a decline in cognitive functions, mainly the person’s memory and intelligence, due to the death of brain cells. An intermediate stage called mild cognitive impairment was found between the normal cognitive and dementia. Subjects in this stage are not demented but exhibit a decline in memory beyond that expected at their age and education [2, 3]. Mild cognitive impairment is an earlier stage, which may progress to dementia [4]. Psychometric predictors and clinical evaluation in elderly subjects can predict mild cognitive impairment [5]. Mild cognitive impairment and dementia can be detected using EEG biomarkers [6,7,8]. Mini Mental State Examination (MMSE), Clinical Dementia Rating (CDR), and Global Deterioration
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