Impact of brain regions on attention deficit hyperactivity disorder (ADHD) electroencephalogram (EEG) signals: Comparison of machine learning algorithms with empirical mode decomposition and time domain analysis.

Journal: Applied neuropsychology. Child
Published Date: Jun 16, 2025

Abstract

OBJECTIVE: This study emphasizes the importance of using proper combinations of brain area, extraction of features, and machine learning (ML) techniques for electroencephalogram (EEG)-based attention deficit hyperactivity disorder (ADHD) identification. The effectiveness of EEG-based solutions is determined by the feature extraction method, selection of brain regions, and ML algorithms used.

Authors

  • Manjusha Deshmukh
    Computer Engineering Department, Saraswati College of Engineering, Navi Mumbai, India.
  • Mahi Khemchandani
    Information Technology, Saraswati College of Engineering, Navi Mumbai, India.
  • Mitali Mhatre
    Mechanical Engineering Department, Saraswati College of Engineering, Navi Mumbai, India.

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