Electroencephalogram-Based ConvMixer Architecture for Recognizing Attention Deficit Hyperactivity Disorder in Children

Electroencephalogram-Based ConvMixer Architecture for Recognizing Attention Deficit Hyperactivity Disorder in Children

Attention deficit hyperactivity disorder (ADHD) is a neuro-developmental disorder that affects approximately 5–10% of school-aged children worldwide. Early diagnosis and intervention are essential to improve the quality of life of patients and their families. In this study, we propose ConvMixer-ECA,...

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Bibliographic Details
Main Authors: Min Feng, Juncai Xu
Format: Article
Language:English
Published: MDPI AG 2024-05-01
Series:Brain Sciences
Subjects:
attention deficit hyperactivity disorder (ADHD)
ConvMixer
efficient channel attention (ECA)
electroencephalogram (EEG)
deep learning
early diagnosis
Online Access:https://www.mdpi.com/2076-3425/14/5/469

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https://www.mdpi.com/2076-3425/14/5/469

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