PhysioEx

PhysioEx ( Physiological Signal Explainer ) is a versatile python library tailored for building, training, and explaining deep learning models for physiological signal analysis.

The main purpose of the library is to propose a standard and fast methodology to train and evalutate state-of-the-art deep learning architectures for physiological signal analysis, to shift the attention from the architecture building task to the explainability task.

With PhysioEx you can simulate a state-of-the-art experiment just running the train command; evaluating and saving the trained model; and start focusing on the explainability task! The train command will also take charge of downloading and processing the specified dataset if unavailable.

Supported deep learning architectures

• Chambon2018 model for sleep stage classification.
• TinySleepNet model for sleep stage classification.
• SeqSleepNet model for sleep stage classification (time-frequency images as input).
• SeqECGnet model for ECG arrythmia classifiaction ( 5-AAMI classes ).

Supported datasets

• SleepEDF (version 2018-2013) sleep staging dataset.
• Dreem (version DODO-DODH) sleep staging dataset.
• MIT-BIH Arrhythmia Database dataset for ECG analysis.

Installation guidelines

1. Clone the Repository:

      git clone https://github.com/guidogagl/physioex.git
      cd physioex
   

2. Create a Virtual Environment (Optional but Recommended)

       conda create -n physioex python==3.10
       conda activate physioex
       conda install pip
       pip install --upgrade pip  # On Windows, use `venv\Scripts\activate`
   

3. Install Dependencies and Package in Development Mode

       pip install -e .