An Intelligent Model to Diagnose the Brain Connections Disorders in ADHD People in Different Frequency Bands

Articles in Press

Document Type : Original Article

Author

Department of Computer Engineering, Fouman and Shaft Branch, Islamic Azad University, Fouman, Iran

Abstract

Attention deficit hyperactivity disorder is a neurodevelopmental disorder that typically begins in early childhood and poses significant challenges during school years. This disorder is characterized by impulsive behaviors, inattention, and difficulties with concentration. Early diagnosis and prompt treatment can effectively manage this condition. Accurate diagnosis of ADHD can be achieved through the precise analysis of electroencephalography signals. This article proposes a brain modeling approach using a cellular neural network in various frequency bands to diagnose ADHD. Firstly, the inter-area connections in the brains of individuals with hyperactivity are estimated by assessing the spectral coherence function between channels. Subsequently, the intra-area connections are obtained using a cellular neural network. The results obtained indicate that the intra and inter-area connections in the central, frontal, and parietal regions of the brains of individuals with hyperactivity differ from those of normal individuals in the beta and gamma frequency bands. Consequently, it can be inferred that the presence of disparities in intra and inter-area connections between the brains of individuals with ADHD and normal individuals results in distinct brain functionality within these two groups.

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Soft Computing Journal

Articles in Press, Accepted Manuscript
Available Online from 23 July 2024

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History

  • Receive Date: 17 August 2023
  • Revise Date: 15 February 2024
  • Accept Date: 29 February 2024

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