@inproceedings{08dec4d218834f2eacd8955a162aff6c,
title = "Statistical Spectral and Coherence Analysis of Electroencephalography (EEG) Data: Neural Biomarkers of Attention Deficit Hyperactivity Disorder (ADHD)",
abstract = "Electroencephalography (EEG) is a non-invasive tool widely used for studying brain activity, offering high temporal resolution for real-time analysis of neural dynamics. This study investigates the neurophysiological underpinnings of Attention Deficit Hyperactivity Disorder (ADHD) through statistical spectral and coherence analysis of EEG data. By focusing on frequency bands, we identified distinct patterns in ADHD subjects, including increased beta and alpha power, reduced gamma activity, and altered connectivity in key brain regions. These findings underscore the potential of EEG-based biomarkers for improving ADHD diagnosis and treatment strategies.",
keywords = "ADHD diagnosis, coherence analysis, EEG, neural biomarkers, spectral analysis",
author = "Fai Alismail and Hernando Ombao",
note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024 ; Conference date: 03-12-2024 Through 06-12-2024",
year = "2024",
doi = "10.1109/BIBM62325.2024.10822425",
language = "English (US)",
series = "Proceedings - 2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "7032--7034",
editor = "Mario Cannataro and Huiru Zheng and Lin Gao and Jianlin Cheng and \{de Miranda\}, \{Joao Luis\} and Ester Zumpano and Xiaohua Hu and Young-Rae Cho and Taesung Park",
booktitle = "Proceedings - 2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024",
address = "United States",
}