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PhysioEx, a PyTorch Lightning based library for Interpretable physiological signal classifiers

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PhysioEx

Python Version PyPI Version

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, test_model and finetune commands; evaluating and saving the trained model; and start focusing on the explainability task!

Supported deep learning architectures

  • Chambon2018 model for sleep stage classification ( raw time series as input).
  • TinySleepNet model for sleep stage classification (raw time series as input).
  • SeqSleepNet model for sleep stage classification (time-frequency images as input).

Supported datasets

For the public available datasets ( DCSM, HMC ) PhysioEx takes care of automatically download the data thanks to the preprocess command. The other datasets needs to be acquired first ( mostly on NSSR ) and then fetched by PhysioEx via the preprocess command.

Installation guidelines

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`

Install via pip

  1. Install PhysioEx from PyPI:
pip install physioex

Install from source

  1. Clone the Repository:
   git clone https://github.com/guidogagl/physioex.git
   cd physioex
  1. Install Dependencies and Package in Development Mode
    pip install -e .

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PhysioEx, a PyTorch Lightning based library for Interpretable physiological signal classifiers

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