Entropy and Coherence Features in EEG-Based Classification for Alzheimer's Disease Detection-Reference-Cited by-同舟云学术

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Entropy and Coherence Features in EEG-Based Classification for Alzheimer's Disease Detection

Published:2024-05-20 Issue: Volume: Page:
ISSN:
Container-title:2024 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)
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Author:

Criscuolo Sabatina¹,Cataldo Andrea²,De Benedetto Egidio¹,Masciullo Antonio²,Pesola Marisa¹,Schiavoni Raissa²

Affiliation:

1. University of Naples Federico II,Department of Electrical Engineering and Information Technology (DIETI),Naples,Italy

2. University of Salento,Department of Engineering for Innovation,Lecce,Italy

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10560479/10560519/10560664.pdf?arnumber=10560664

Reference32 articles.

1. Alzheimer disease

2. Mini-Mental State Examination (MMSE) for the early detection of dementia in people with mild cognitive impairment (MCI)

3. Potential New Approaches for Diagnosis of Alzheimer's Disease and Related Dementias

4. A systematic review and methodological analysis of EEG-based biomarkers of Alzheimer's disease

5. A Method for Optimizing the Artifact Subspace Reconstruction Performance in Low-Density EEG

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. LEADNet: Detection of Alzheimer’s Disease Using Spatiotemporal EEG Analysis and Low-Complexity CNN;IEEE Access;2024

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