Automated depression detection via cloud based EEG analysis with transfer learning and synchrosqueezed wavelet transform

Automated depression detection via cloud based EEG analysis with transfer learning and synchrosqueezed wavelet transform

Abstract Post-COVID-19, depression rates have risen sharply, increasing the need for early diagnosis using electroencephalogram (EEG) and deep learning. To tackle this, we developed a cloud-based computer-aided depression diagnostic (CCADD) system that utilizes EEG signals from local databases. This...

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Bibliographic Details
Main Authors: Sara Bagherzadeh, Mohammad Reza Norouzi, Amirhesam Ghasri, Pouya Tolou Kouroshi, Sepideh Bahri Hampa, Fatemeh Farokhshad, Ahmad Shalbaf
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:Scientific Reports
Subjects:
Convolutional neural network (CNN)
Depression detection
Deep learning (DL)
Electroencephalogram (EEG)
Synchrosqueezing wavelet transform (SSWT)
Online Access:https://doi.org/10.1038/s41598-025-02452-7
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https://doi.org/10.1038/s41598-025-02452-7

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