A Dataset of Scalp EEG Recordings of Alzheimer’s Disease, Frontotemporal Dementia and Healthy Subjects from Routine EEG

• Published in: Data (Basel) Vol. 8; no. 6; p. 95
• Main Authors: Miltiadous, Andreas, Tzimourta, Katerina D., Afrantou, Theodora, Ioannidis, Panagiotis, Grigoriadis, Nikolaos, Tsalikakis, Dimitrios G., Angelidis, Pantelis, Tsipouras, Markos G., Glavas, Euripidis, Giannakeas, Nikolaos, Tzallas, Alexandros T.
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.05.2023
• Subjects: Alzheimer's disease; Brain research; Data collection; Datasets; Dementia; Electroencephalography; frontotemporal dementia; Illnesses; Independent component analysis; Machine learning; Magnetic resonance imaging; Medical imaging; Metadata; Neuroimaging; Neuropsychology; Open source software; Physiological aspects; Quality control; resting state; routine EEG; Greece
• ISSN: 2306-5729; 2306-5729
• DOI: 10.3390/data8060095

Recently, there has been a growing research interest in utilizing the electroencephalogram (EEG) as a non-invasive diagnostic tool for neurodegenerative diseases. This article provides a detailed description of a resting-state EEG dataset of individuals with Alzheimer’s disease and frontotemporal de...