A Tensor Decomposition Scheme for EEG-Based Diagnosis of Mild Cognitive Impairment
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Elsevier BV
Abstract
Mild Cognitive Impairment (MCI) is the primary stage of acute Alzheimer's disease, and early detection is crucial for the person and those around him. It is difficult to recognize since this mild stage does not have clear clinical signs, and its symptoms are between normal aging and severe dementia. Here, we propose a tensor decomposition-based scheme for automatically diagnosing MCI using Electroencephalogram (EEG) signals. A new projection is proposed, which preserves the spatial information of the electrodes to construct a data tensor. Then, using parallel factor analysis (PARAFAC) tensor decomposition, the features are extracted, and a support vector machine (SVM) is used to discriminate MCI from normal subjects. The proposed scheme was tested on two different datasets. The results showed that the tensor-based method outperformed conventional methods in diagnosing MCI with an average classification accuracy of 93.96% and 78.65% for the first and second datasets, respectively. Therefore, it seems that maintaining the spatial topology of the signals plays a vital role in the processing of EEG signals.Description
Keywords
Alzheimer's disease, Electroencephalogram (EEG), Mild cognitive impairment (MCI), Parallel factor analysis (PARAFAC), Tensor decomposition, 46 Information and Computing Sciences, 3208 Medical Physiology, 32 Biomedical and Clinical Sciences, Clinical Research, Alzheimer's Disease, Aging, Neurosciences, Acquired Cognitive Impairment, Dementia, Neurodegenerative, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Brain Disorders, Bioengineering, 4.1 Discovery and preclinical testing of markers and technologies, Neurological
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Heliyon, ISSN: 2405-8440 (Print); 2405-8440 (Online), Elsevier BV, 10(4), e26365-. doi: 10.1016/j.heliyon.2024.e26365
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© 2024 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).