"Project 7: Artificial intelligence-based techniques for neglect identification" @ Brain Hack Warsaw

This repository contains the code developed for generalise Eye-tracking trajectory analysis and classification techniques, inspired to the one developed and used for the paper: "Machine learning algorithms on eye tracking trajectories to classify patients with spatial neglect".

Please cite the paper if you are using either our dataset, preprocessing or model.

Data

Preprocessing of trajectories

You can download the dataset used for the preprocessing script from this link. For a quick test of the preprocessing, we also uploaded 4 subjects (2 healthy and 2 with neglect) inside the folder.

Machine Learning classification

If users are only interested in running the classification script, they can find the dataset inside the ML_Analysis/dataset_preprocessed_trajectories.

Usage

1) Preprocessing of trajectories

To run the preprocessing of the trajectories, users can simply run the following script, located inside this folder:

main.m

This file loads tre trajectories from the Dataset folder and calls the preprocessing function preprocessing.m for every subject.

The preprocessing can be performed in python, runnin the script located inside this folder

2) Machine Learning classification

To run the classification script, users can utilize the script located inside this folder and run in Spider:

Cnn_and_ML_analysis.ipynb

For full Machine Learning and Deep Learning processing, please refer to the following repo