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Communication Dans Un Congrès Année : 2023

New MCI Detection Method Based on Transformer and EEG Data

Résumé

Preventing health issues is a crucial aspect of the medical field, particularly when it comes to mild cognitive impairment (MCI), which is a risk factor for developing dementia. Early detection of MCI is essential, and there are two types of MCI: amnestic MCI (aMCI) and non-amnestic MCI (naMCI). However, it is challenging to differentiate between individuals with MCI and those who are aging normally. Electroencephalography (EEG) is a promising modality for diagnosing MCI, which provides information about an individual's cognitive state during a clinical examination. This research aims to distinguish between individuals diagnosed with MCI as either aMCI or naMCI, and healthy controls (HC) during a verbal fluency task (VFT). To achieve this, a new MCI detection method based on the transformer architecture was proposed. This method makes use of EEG data and achieves up to 94.78% accuracy.
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Dates et versions

hal-04338180 , version 1 (12-12-2023)

Identifiants

Citer

Siwar Chaabene, Brahim Haroun Hassan, Amal Boudaya, Lotfi Chaâri, Bassem Bouaziz. New MCI Detection Method Based on Transformer and EEG Data. 31st European Signal Processing Conference (EUSIPCO 2023), Sep 2023, Helsinki, Finland. pp.1200-1204, ⟨10.23919/EUSIPCO58844.2023.10290024⟩. ⟨hal-04338180⟩
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