# DeprNet: A Deep Convolution Neural Network Framework for Detecting Depression Using EEG

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/deprnet-a-deep-convolution-neural-network-framework-for-detecting-depression/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Ayan Seal,Rishabh Bajpai,Jagriti Agnihotri,Anis Yazidi,Enrique Herrera‐Viedma,Ondřej Krejcar |
| Citations | 256 |
| DOI | 10.1109/tim.2021.3053999 |
| Fields | Medicine,Neuroscience |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W3126085817 |
| Type | article |
| Year | 2021 |

## Paper authors

- [Ayan Seal](https://scholariq.org/researchers/ayan-seal/)

## Paper journal

- [IEEE Transactions on Instrumentation and Measurement](https://scholariq.org/journals/ieee-transactions-on-instrumentation-and-measurement/)

## Paper primary topic

- [EEG and Brain-Computer Interfaces](https://scholariq.org/topics/eeg-and-brain-computer-interfaces/)

## Paper topics

- [EEG and Brain-Computer Interfaces](https://scholariq.org/topics/eeg-and-brain-computer-interfaces/)
- [ECG Monitoring and Analysis](https://scholariq.org/topics/ecg-monitoring-and-analysis/)
- [Functional Brain Connectivity Studies](https://scholariq.org/topics/functional-brain-connectivity-studies/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.