Wavelet Energy and Wavelet Coherence as EEG Biomarkers for the Diagnosis of Parkinson's Disease-Related Dementia and Alzheimer's Disease

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Parkinson's disease (PD) and Alzheimer's disease (AD) can coexist in severely affected; elderly patients. Since they have different pathological causes and lesions and consequently require different treatments; it is critical to distinguish PD-related dementia (PD-D) from AD. Conventional electroencephalograph (EEG) analysis has produced poor results. This study investigated the possibility of using relative wavelet energy (RWE) and wavelet coherence (WC) analysis to distinguish between PD-D patients; AD patients and healthy elderly subjects. In EEG signals; we found that low-frequency wavelet energy increased and high-frequency wavelet energy decreased in PD-D patients and AD patients relative to healthy subjects. This result suggests that cognitive decline in both diseases is potentially related to slow EEG activity; which is consistent with previous studies. More importantly; WC values were lower in AD patients and higher in PD-D patients compared with healthy subjects. In particular; AD patients exhibited decreased WC primarily in the band and in links related to frontal regions; while PD-D patients exhibited increased WC primarily in the and bands and in temporo-parietal links. Linear discriminant analysis (LDA) of RWE produced a maximum accuracy of 79.18% for diagnosing PD-D and 81.25% for diagnosing AD. The discriminant accuracy was 73.40% with 78.78% sensitivity and 69.47% specificity. In distinguishing between the two diseases; the maximum performance of LDA using WC was 80.19%. We suggest that using a wavelet approach to evaluate EEG results may facilitate discrimination between PD-D and AD. In particular; RWE is useful for differentiating individuals with and without dementia and WC is useful for differentiating between PD-D and AD.
Publisher
MDPI AG
Issue Date
2016-01
Language
English
Article Type
Article
Keywords

MILD COGNITIVE IMPAIRMENT; EARLY-STAGE; FUNCTIONAL CONNECTIVITY; FREQUENCY-ANALYSIS; BRAIN ACTIVITY; RESTING EEG; STATE; SYNCHRONIZATION; DYNAMICS; SERIES

Citation

ENTROPY, v.18, no.1

ISSN
1099-4300
DOI
10.3390/e18010008
URI
http://hdl.handle.net/10203/208029
Appears in Collection
BiS-Journal Papers(저널논문)
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