CNNs-on-CHB-MIT

# CNNs-on-CHB-MIT The project is about applying CNNs to EEG data from CHB-MIT to predict seizure. It's a group project assigned at UNIVERSITA' DI CAMERINO for computer science bachelor. The objective of the project was to try to replicate the result obtained in the paper: [Truong, Nhan Duy, et al. "Convolutional neural networks for seizure prediction using intracranial and scalp electroencephalogram." Neural Networks 105 (2018): 104-111.](https://www.sciencedirect.com/science/article/pii/S0893608018301485) The algorithm consist to create spectograms of the data and than use them with a CNN model to predict seizure. More information are in [presentazione.pdf](presentazione.pdf) and [relazione.pdf](relazione.pdf). The two file are respectively the presentation and the relation of the work in italian language. ## Getting Started ### Prerequisites In the project anaconda was used to managed the packages. Packages required: * keras 2.2.2 * python 3.6.6 * tensorflow 1.10.0 * matplotlib * numpy * pyedflib * scipy For the evaluation of the network, training and testing, the GPU is used to have a fast evaluation. By using the CPU the training time is a lot more slowly than using GPU. Packages required for GPU: * tensorflow-GPU For the using of the GPU this link was very useful to install all the driver for Ubuntu 18.04 LTS https://medium.com/@naomi.fridman/install-conda-tensorflow-gpu-and-keras-on-ubuntu-18-04-1b403e740e25 (Note that the GPU used was GTX 850M so I can't ensure that the guide linked will work for different hardware). ### Installing Download or clone the repository on your computer and set the parameters: * [PARAMETERS_DATA_EDITING.txt](PARAMETERS_DATA_EDITING.txt): contain the parameters for the creation of the spectograms: - **pathDataSet**: path of the folder containing the dataset; - **FirstPartPathOutput**: path of the folder where spectograms will be saved; * [PARAMETERS_CNN.txt](PARAMETERS_CNN.txt): contain the parameters for the use of CNN: - **PathSpectogramFolder**: Path of the folder containing the spectograms; - **OutputPath**: file where to save the results; - **OutputPathModels**: where to save the CNN models. ## Recovering data The dataset is downloadable from this site: [https://archive.physionet.org/pn6/chbmit/](https://archive.physionet.org/pn6/chbmit/). To get all the data it's suggested to use this command: ``` wget -r --no-parent https://archive.physionet.org/pn6/chbmit/ ``` In the code only patients 1, 2, 5, 19, 21, 23 are used, the others are discarded for problems in the data. **NOTE**: For the patient 19 replace the summary file(chb19-summary.txt) with the one in this repository inside the folder summaryChanged. ## Running After setted all the parameters run the code. ``` python DataserToSpectogram.py #Creation of the spectograms python CNN.py #Creation of the CNN and evaluation of the model on the spectograms python TestThreshold.py #Search the best thresold for each patient ``` ## Contributing Please read [CONTRIBUTING.md](https://gist.github.com/PurpleBooth/b24679402957c63ec426) for details on our code of conduct, and the process for submitting pull requests to us. ## Authors * [**Simone Morettini**](https://github.com/MesSem) * [**Alessandra Renieri**](https://github.com/a311987) ## License This project is licensed under the GNU GENERAL PUBLIC LICENSE - see the [LICENSE.md](LICENSE.md) file for details <!--- ## Acknowledgments * ______ --->