Impact of EEG Parameters Detecting Dementia Diseases: A Systematic Review

Dementia diseases are increasing rapidly, according to the World Health Organization (WHO), becoming an alarming problem for the health sector. The electroencephalogram (EEG) is a non-invasive test that records brain electrical activity and has a wide field of applications in the medical area, one o...

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Bibliographic Details
Published in:IEEE access 2021, Vol.9, p.78060-78074
Main Authors: Sanchez-Reyes, Luz-Maria, Rodriguez-Resendiz, Juvenal, Avecilla-Ramirez, Gloria Nelida, Garcia-Gomar, Maria-Luisa, Robles-Ocampo, Jose-Billerman
Format: Article
Language:English
Subjects:
automatic/semi-automatic detection
biomedical applications
Classification
Dementia
detection reliability
EEG systems
Electrodes
Electroencephalography
Feature extraction
neurodegenerative diseases
Parameters
Reliability
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Summary:Dementia diseases are increasing rapidly, according to the World Health Organization (WHO), becoming an alarming problem for the health sector. The electroencephalogram (EEG) is a non-invasive test that records brain electrical activity and has a wide field of applications in the medical area, one of which is the detection of neurodegenerative diseases. The aim of this work is to present the results of a thorough review of the use of EEG systems for the detection of dementia diseases. Around 82 papers published between 2009 and 2020 were reviewed and compared obtaining data such as sampling time, number of electrodes, the most popular processing, classification, and validation techniques, as well as an analysis of the reported results. The relationship of the selected parameters with the efficiency obtained is shown. Some more common combinations in the reviewed papers that demonstrated to have reliability levels greater than 90%, and details to be considered at each stage of the process. An overview of the most commonly used classification tools and processing techniques is also described.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2021.3083519