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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,...

Ausführliche Beschreibung

Gespeichert in:
Hauptverfasser: Min Feng, Juncai Xu
Format: Artigo
Sprache:Inglês
Veröffentlicht: MDPI AG 2024-05-01
Schriftenreihe:Brain Sciences
Schlagworte:
attention deficit hyperactivity disorder (ADHD)
ConvMixer
efficient channel attention (ECA)
electroencephalogram (EEG)
deep learning
early diagnosis
Online-Zugang:https://www.mdpi.com/2076-3425/14/5/469
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