Key result
Mobile Net V2 neural network using EEG spectrograms achieves ~91% accuracy diagnosing major depressive disorder.
Why the study?
Early diagnosis of depression is critical, yet data collection is challenging because patients struggle to stay still, prompting the need for models using limited EEG electrodes.
Does a Mobile Net V2 CNN model using EEG spectrograms accurately diagnose Major Depressive Disorder compared to healthy controls?
Does a Mobile Net V2 CNN model using EEG spectrograms accurately diagnose Major Depressive Disorder compared to healthy controls?
A Mobile Net V2 convolutional neural network using EEG spectrograms can diagnose Major Depressive Disorder with 91% accuracy.
May support EEG-based CNN screening for MDD; leaves open prospective validation before clinical use.
Not only is early diagnosis of Depression a critical issue as it is a fast-growing disease in this current decade, but also collecting data from this group of patients is very challenging as they cannot be relaxing and stay still. In this study, we aimed to use a limited number of Electroencephalography (EEG) electrodes to make it easier for the clinician and patient and develop a Conventional Neural Network (CNN) model to help the clinician to have a more accurate diagnosis of the disease. For this aim, we used two public EEG data of people with Major Depressive Disorder (MDD). Totally, the EEG data of 91 subjects (38 healthy and 53 MDD) were utilized in our study. After preprocessing, the spectrogram of EEG was used as input for the CNN model which was Mobile Net V2. The highest validation accuracy we could get was 91 % with a learning rate and batch size of 0.0001 and 32, respectively. Our results demonstrate that Mobile NET may have a high performance in MDD diagnosis.
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Hatami et al. (2023) studied Major Depressive Disorder (n=91). Mobile Net V2 CNN model was evaluated on Validation accuracy. A Mobile Net V2 convolutional neural network using EEG spectrograms achieved a highest validation accuracy of 91% for diagnosing Major Depressive Disorder.
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