A Review of Methods of Diagnosis and Complexity Analysis of Alzheimer’s Disease Using EEG Signals
This study will concentrate on recent research on EEG signals for Alzheimer’s diagnosis, identifying and comparing key steps of EEG-based Alzheimer’s disease (AD) detection, such as EEG signal acquisition, preprocessing function extraction, and classification methods. Furthermore, highlighting gener...
Saved in:
Main Authors: | Mahshad Ouchani, Shahriar Gharibzadeh, Mahdieh Jamshidi, Morteza Amini |
---|---|
Format: | article |
Language: | EN |
Published: |
Hindawi Limited
2021
|
Subjects: | |
Online Access: | https://doaj.org/article/f0e1024f60fc44f68d67bb1306b70b45 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Classification methods for ongoing EEG and MEG signals
by: BESSERVE,MICHEL, et al.
Published: (2007) -
EEG machine learning for accurate detection of cholinergic intervention and Alzheimer’s disease
by: Sonja Simpraga, et al.
Published: (2017) -
Automatic Diagnosis of Schizophrenia in EEG Signals Using CNN-LSTM Models
by: Afshin Shoeibi, et al.
Published: (2021) -
Characterizing Alzheimer's disease severity via resting-awake EEG amplitude modulation analysis.
by: Francisco J Fraga, et al.
Published: (2013) -
Detecting Phase-Synchrony Connectivity Anomalies in EEG Signals. Application to Dyslexia Diagnosis
by: Marco A. Formoso, et al.
Published: (2021)