Brain entropy, fractal dimensions and predictability: A review of complexity measures for EEG in healthy and neuropsychiatric populations-Reference-Cited by-同舟云学术

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Brain entropy, fractal dimensions and predictability: A review of complexity measures for EEG in healthy and neuropsychiatric populations

Published:2022-09-02 Issue:7 Volume:56 Page:5047-5069
ISSN:0953-816X
Container-title:European Journal of Neuroscience
language:en
Short-container-title:Eur J of Neuroscience

Author:

Lau Zen J.¹^ORCID,Pham Tam¹^ORCID,Chen S. H. Annabel¹²³⁴^ORCID,Makowski Dominique¹^ORCID

Affiliation:

1. School of Social Sciences Nanyang Technological University Singapore

2. Centre for Research and Development in Learning Nanyang Technological University Singapore

3. Lee Kong Chian School of Medicine Nanyang Technological University Singapore

4. National Institute of Education Nanyang Technological University Singapore

Publisher

Wiley

Subject

General Neuroscience

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/ejn.15800

Reference231 articles.

1. EEG Signal Diversity Varies With Sleep Stage and Aspects of Dream Experience

2. Analysis of EEG background activity in Alzheimer's disease patients with Lempel–Ziv complexity and central tendency measure

3. Use of the fractal dimension for the analysis of electroencephalographic time series

4. Non-linear analysis of EEG signals at various sleep stages

5. Automated Prediction of Sudden Cardiac Death Risk Using Kolmogorov Complexity and Recurrence Quantification Analysis Features Extracted from HRV Signals

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