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https://github.com/simula/rest


https://github.com/simula/rest

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README

          

# REST

# Elite Female Football Athletes Dataset and Analysis Tools

This repository contains various scripts and tools for analyzing a novel dataset of 21 elite female football athletes. The dataset comprises 17 days of actigraphy, well-being, caffeine consumption, screen time, and daily hand strength test data. The aim is to provide a comprehensive understanding of the interplay between lifestyle factors, sleep, and athletic performance.

## Repository Structure
- `algorithms`: The folder contains several sleep detection algorithms and non wear algorithms. Additional, it provides sleep statistic functions and a base class to load in the actigraphy files.
- `data_preprocessing`: Script for preprocessing and loading in of the original gt3x files. Addditional, a list of visualisations.
- `generate_reports.py`: Example script how to read in actigraphy files and generate sleep statistics, sleep annotations and plots.

- `technical_validation.py`: Script for performing technical validation of data or models. The script reproduces the figures and results of the paper.

- `annonymisation.py`: Script for anonymizing sensitive data. It applies techniques to remove or obfuscate personally which we used for the annonymisation of the data.

- `transfer_learning_inference.py`: Script for performing inference using transfer learning models. It applies a LSTM model which has been trained on the MESA sleep study to REST for sleep prediction.

## Installation

1. Clone the repository:

```bash
git clone https://github.com/simula/REST.git
cd REST
```

2. Create and activate a virtual environment:

```bash
conda env create -f environment.yml
```
## Usage