Data Sheet 1_The use of low-density EEG for the classification of PPA and MCI.docx

Data Sheet 1_The use of low-density EEG for the classification of PPA and MCI.docx

Objective<p>Dissociating Primary Progressive Aphasia (PPA) from Mild Cognitive Impairment (MCI) is an important, yet challenging task. Given the need for low-cost and time-efficient classification, we used low-density electroencephalography (EEG) recordings to automatically classify PPA, MCI a...

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Bibliographic Details
Main Author: Panteleimon Chriskos (17251084) (author)
Other Authors: Kyriaki Neophytou (6377588) (author), Christos A. Frantzidis (10780023) (author), Jessica Gallegos (20688188) (author), Alexandros Afthinos (13806361) (author), Chiadi U. Onyike (20688191) (author), Argye Hillis (10471100) (author), Panagiotis D. Bamidis (9988646) (author), Kyrana Tsapkini (6831107) (author)
Published: 2025
Subjects:
Neurocognitive Patterns and Neural Networks
primary progressive aphasia
mild cognitive impairment
classification
electroencephalography (EEG)
functional connectivity
energy rhythms
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