Early diagnosis of Alzheimer's disease and mild cognitive impairment based on electroencephalography : From the perspective of event related potentials and deep learning
Copyright © 2022 Elsevier B.V. All rights reserved..
Alzheimer's disease (AD), a neurodegenerative disorder characterized by progressive cognitive decline, is generally prevalent in elderly people with significant disability and mortality. There is no effective treatment for AD currently, but the early diagnosis might be beneficial for delaying the disease progression. Apart from invasive laboratory tests and expensive neuroimaging examination, the electroencephalography (EEG) and event related potentials (ERPs) have emerged as promising approaches for the early detection of AD as well as mild cognitive impairment (MCI), due to its affordability, noninvasively, and superior temporal resolution. In addition, the recent advent of deep learning architectures further improves the accuracy of AD and MCI diagnosis. This article reviewed the application of EEG signal for the early diagnosis of AD and MCI, especially focusing on ERPs and deep learning. Furthermore, recommendation for further research to recruit the combination of ERP components and deep leaning models in diagnosing AD and MCI was proposed and highlighted.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2022 |
|---|---|
| Erschienen: |
2022 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:182 |
|---|---|
| Enthalten in: |
International journal of psychophysiology : official journal of the International Organization of Psychophysiology - 182(2022) vom: 01. Dez., Seite 182-189 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Wang, Chu [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
Alzheimer's disease |
|---|
| Anmerkungen: |
Date Completed 29.11.2022 Date Revised 15.12.2022 published: Print-Electronic Citation Status MEDLINE |
|---|
| doi: |
10.1016/j.ijpsycho.2022.10.010 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM348234619 |
|---|
| LEADER | 01000naa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM348234619 | ||
| 003 | DE-627 | ||
| 005 | 20231226035711.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 231226s2022 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1016/j.ijpsycho.2022.10.010 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1160.xml |
| 035 | |a (DE-627)NLM348234619 | ||
| 035 | |a (NLM)36309183 | ||
| 035 | |a (PII)S0167-8760(22)00247-1 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Wang, Chu |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Early diagnosis of Alzheimer's disease and mild cognitive impairment based on electroencephalography |b From the perspective of event related potentials and deep learning |
| 264 | 1 | |c 2022 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Completed 29.11.2022 | ||
| 500 | |a Date Revised 15.12.2022 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2022 Elsevier B.V. All rights reserved. | ||
| 520 | |a Alzheimer's disease (AD), a neurodegenerative disorder characterized by progressive cognitive decline, is generally prevalent in elderly people with significant disability and mortality. There is no effective treatment for AD currently, but the early diagnosis might be beneficial for delaying the disease progression. Apart from invasive laboratory tests and expensive neuroimaging examination, the electroencephalography (EEG) and event related potentials (ERPs) have emerged as promising approaches for the early detection of AD as well as mild cognitive impairment (MCI), due to its affordability, noninvasively, and superior temporal resolution. In addition, the recent advent of deep learning architectures further improves the accuracy of AD and MCI diagnosis. This article reviewed the application of EEG signal for the early diagnosis of AD and MCI, especially focusing on ERPs and deep learning. Furthermore, recommendation for further research to recruit the combination of ERP components and deep leaning models in diagnosing AD and MCI was proposed and highlighted | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Review | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 650 | 4 | |a Alzheimer's disease | |
| 650 | 4 | |a Deep learning | |
| 650 | 4 | |a Early diagnosis | |
| 650 | 4 | |a Event related potentials | |
| 650 | 4 | |a Mild cognitive impairment | |
| 700 | 1 | |a Xu, Tao |e verfasserin |4 aut | |
| 700 | 1 | |a Yu, Wen |e verfasserin |4 aut | |
| 700 | 1 | |a Li, Ting |e verfasserin |4 aut | |
| 700 | 1 | |a Han, Huan |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Min |e verfasserin |4 aut | |
| 700 | 1 | |a Tao, Ming |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t International journal of psychophysiology : official journal of the International Organization of Psychophysiology |d 1993 |g 182(2022) vom: 01. Dez., Seite 182-189 |w (DE-627)NLM013811800 |x 1872-7697 |7 nnns |
| 773 | 1 | 8 | |g volume:182 |g year:2022 |g day:01 |g month:12 |g pages:182-189 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1016/j.ijpsycho.2022.10.010 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 182 |j 2022 |b 01 |c 12 |h 182-189 | ||