Automatic Depression Detection by Multi-model Ensemble. Based on DAIC-WOZ dataset.

[ACL'19] [PyTorch] Multimodal Transformer

中文文本分类，TextCNN，TextRNN，FastText，TextRCNN，BiLSTM_Attention，DPCNN，Transformer，基于pytorch，开箱即用。

An implementation of vggish in keras with tf backend

A research study aiming to discover distinguishable pattern between pre and post diagnosis behavior of self-diagnosed individuals with depression on Twitter

Repository for CS224S project: Detecting anxiety from short clips of free-form speech

ML Model using NLP and Sentiment Analysis.

Anxiety detection using Deep learning

Machine learning models to detect anxiety and depression through text.

Pattern recognition and analysis of EEG signals from PTSD patients

Depression Detection from Speech

A module to compute lexical availability score from texts

This repository contains the code for the paper `End-to-End Multimodal Emotion Recognition using Deep Neural Networks`.

Baseline scripts for the Audio/Visual Emotion Challenge 2019

This is an implementation of the attention-based hybrid architecture (Ghosh et al, 2023) for suicide/depressive social media notes detection.

Official source code for the paper: "Reading Between the Frames Multi-Modal Non-Verbal Depression Detection in Videos"

Official source code for the paper: "It’s Just a Matter of Time: Detecting Depression with Time-Enriched Multimodal Transformers"

A python script to process raw ECG signals and impute the peaks and heartbeats following noise suppression to obtain processed ECG

Brain Computer Interaction project : engage and stop a hand exoskeleton though ECG signal decoding.

Predicting Cardiac Wellnes: Using a Multi-Layer Perceptron on ECG Data

Evaluation of different deep learning based approaches for classifying ECG signals from MIT-BIH Arrythimia database and PTB Diagnostic ECG Database. Authors: Mert Ertugrul, Johan Lokna, Nora Schneider