Using Electroencephalogram-Extracted Nonlinear Complexity and Wavelet-Extracted Power Rhythm Features during the Performance of Demanding Cognitive Tasks (Aristotle's Syllogisms) in Optimally Classifying Patients with Anorexia Nervosa.
- DOI
- 10.3390/brainsci14030251
- Published
- 2024 Mar 4
- Container
- Brain sciences
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.3390/brainsci14030251,
title = {Using Electroencephalogram-Extracted Nonlinear Complexity and Wavelet-Extracted Power Rhythm Features during the Performance of Demanding Cognitive Tasks (Aristotle's Syllogisms) in Optimally Classifying Patients with Anorexia Nervosa.},
author = {Karavia A and Papaioannou A and Michopoulos I and Papageorgiou PC and Papaioannou G and Gonidakis F and Papageorgiou CC},
year = {2024},
journal = {Brain sciences},
doi = {10.3390/brainsci14030251},
url = {https://doi.org/10.3390/brainsci14030251}
}RIS
TY - JOUR TI - Using Electroencephalogram-Extracted Nonlinear Complexity and Wavelet-Extracted Power Rhythm Features during the Performance of Demanding Cognitive Tasks (Aristotle's Syllogisms) in Optimally Classifying Patients with Anorexia Nervosa. AU - Karavia A AU - Papaioannou A AU - Michopoulos I AU - Papageorgiou PC AU - Papaioannou G AU - Gonidakis F AU - Papageorgiou CC PY - 2024 JO - Brain sciences DO - 10.3390/brainsci14030251 UR - https://doi.org/10.3390/brainsci14030251 ER -
APA
A, K., A, P., I, M., PC, P., G, P., F, G., & CC, P. (2024). Using Electroencephalogram-Extracted Nonlinear Complexity and Wavelet-Extracted Power Rhythm Features during the Performance of Demanding Cognitive Tasks (Aristotle's Syllogisms) in Optimally Classifying Patients with Anorexia Nervosa.. Brain sciences. https://doi.org/10.3390/brainsci14030251
Source records
- pubmed · retrieved 2026-09-26T05:20:36.664Z