Here is the PyTorch implementation of the EmoHEAL model. EmoHEAL is a lightweight deep learning architecture that uses wrist sensor data and achieves 72.35% accuracy on the K-EmoCon dataset, making it suitable for IoT applications in smartwatches.

1. TCN+CA-SA+GRU Fusion
2. TCN+GRU Fusion
3. TCN+xLSTM
4. TCN+MHA
5. TCN+Transformer Encoder
6. ResNet + GRU Fusion

You can request the dataset from K-Emocon. Place the dataset in the dataset folder.

Dependencies can be installed using the following command:

conda env create -f EmoHEAL.yml