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Related Experiment Video

Updated: Nov 30, 2025

Conscious and Non-conscious Representations of Emotional Faces in Asperger's Syndrome
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Deep-Asymmetry: Asymmetry Matrix Image for Deep Learning Method in Pre-Screening Depression.

Min Kang1, Hyunjin Kwon2, Jin-Hyeok Park2

  • 1Department of Computer Engineering, Gachon University, Sungnam-si 13306, Korea.

Sensors (Basel, Switzerland)
|November 18, 2020
PubMed
Summary

This study introduces a novel deep-asymmetry method for diagnosing depression using electroencephalogram (EEG) asymmetry. The approach achieved 98.85% accuracy in detecting major depressive disorder, offering a promising tool for objective diagnosis.

Area of Science:

  • Neuroscience
  • Machine Learning
  • Medical Diagnostics

Background:

  • Objective diagnosis of depression remains a challenge.
Keywords:
asymmetryasymmetry imageconvolutional neural networksdeep learningelectroencephalogrammajor depressive disorder

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  • Current electroencephalogram (EEG) based methods often rely on one-dimensional data and complex feature extraction.
  • EEG asymmetry is a recognized biomarker for depression.