Related Experiment Video
Updated: Nov 30, 2025
08:31
Conscious and Non-conscious Representations of Emotional Faces in Asperger's Syndrome
Published on: July 31, 2016
14.2K
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
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.
- Current electroencephalogram (EEG) based methods often rely on one-dimensional data and complex feature extraction.
- EEG asymmetry is a recognized biomarker for depression.
