Affect detection

Description

This repository contains the scripts used in this research paper. Please feel free to use it for any academic or commercial projects, and consider citing the paper:

Pinilla, A., Voigt-Antons, J. N., Garcia, J., Raffe, W., & Möller, S. (2023). Real-time affect detection in virtual reality: a technique based on a three-dimensional model of affect and EEG signals. Frontiers in Virtual Reality, 3, 964754. https://doi.org/10.3389/frvir.2022.964754

@article{pinilla_real-time_2023,
	title = {Real-time affect detection in virtual reality: a technique based on a three-dimensional model of affect and {EEG} signals},
	volume = {3},
	issn = {2673-4192},
	shorttitle = {Real-time affect detection in virtual reality},
	url = {https://www.frontiersin.org/articles/10.3389/frvir.2022.964754/full},
	doi = {10.3389/frvir.2022.964754},
	urldate = {2024-01-29},
	journal = {Frontiers in Virtual Reality},
	author = {Pinilla, Andres and Voigt-Antons, Jan-Niklas and Garcia, Jaime and Raffe, William and Möller, Sebastian},
	month = jan,
	year = {2023},
	pages = {964754},
	file = {Full Text:/Users/aepinilla/Zotero/storage/XF5NBVSX/Pinilla et al. - 2023 - Real-time affect detection in virtual reality a t.pdf:application/pdf},
}

NOTE: The preprocessing pipeline used for this experiment was originally implemented in Matlab, using EEGLAB. A more recent Python implementation is available here.

Instructions

1. Install R (https://cran.r-project.org/)
2. Clone this repository:

git clone [email protected]:aepinilla/affect_detection.git

2. Download the 'data.zip' file from the OSF repository of the study: https://osf.io/7v9kt/
3. Unzip data.zip and place it at the root of the folder you just cloned.
4. Using the terminal, go to the root of the 'affect_detection' folder and run the following command:

python main.py

Preprocessing

The 'data' folder contains data that has been already preprocessed. To replicate the preprocessing steps, follow these instructions:

1. Install Matlab.
2. Install EEGLAB following these instructions: https://eeglab.org/tutorials/01_Install/Install.html
3. Transform XDF files to CSV for faster processing:

python xdf_to_csv.py

6. Open EEGLAB in Matlab and run the preprocessing script located at affect_detection/src/preprocessing.m

Reports

All files generated by main.py will be stored in the 'reports' folder. In a MacBook Pro, it took several hours to run the program. If you want to skip that, download the 'reports.zip' file available in the OSF repository: https://osf.io/7v9kt/