Translational Medicine
Open Access

Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

Publications

• Research Article   
  Schizophrenia Diagnosis Utilizing EEG Signals: A Comparison between Time Frequency Convolutional Neural Networks and Transformers
  Author(s): Maryam Saeedi*, Pooya Mohammadi Kazaj, Abdolkarim Saeedi, Arash Maghsoudi and Alireza Vafaei Sadr
  
  Background: Schizophrenia is a chronic mental illness in which a person’s perception of reality is distorted. Early diagnosis can help to manage symptoms and increase long-term treatment. The Electroencephalogram (EEG) is now used to diagnose specific mental disorders. Methods: In this paper, we developed an artificial intelligence methodology built on deep convolutional neural networks and transformer layers to detect schizophrenia from EEG signals directly, recordings include 14 paranoid schizophrenia patients (7 females) with ages ranging from 27 to 32 and 14 normal subjects (7 females) with ages ranging from 26 to 32. In the first phase, we used the Gramian Angular Field (GAF), including two methods: The Gramian Angular Summation Field (GASF) and the Gramian Angular Difference Field (GADF) to represent the EEG signals as various ty.. View More»
  DOI: 10.35248/2161-1025.25.15.341

  Abstract HTML PDF