Code and materials from "Discrimination of sleep and wake periods from a hip-worn raw acceleration sensor using recurrent neural networks"

This repository contains the documentation, code and materials for our paper "Discrimination of sleep and wake periods from a hip-worn raw acceleration sensor using recurrent neural networks". The documentation contains code snippets to load the .gt3x and the data from the Actiwave .edf files and store the data for the subjects that worn both devices in a new HDF5 file BEDTIME_TU7.hdf5 which is compatible with the pandas API. Later notebooks also show how the manual annotation data can be added resulting in a new ANNOTATED_BEDTIME_TU7.hdf5 file. Further notebooks can be found in which the performed experiments are documented and in which the data analysis was conducted.

All code here was developed using conda to make it reproducible. To work with this repository follow the following steps.

Getting Started

1. Clone this repository

git clone https://github.com/Trybnetic/sleep-study.git
cd sleep-study/

2. Install the dependencies

conda create -f environment.yml

3. Activate the environment

conda activate bedtime

4. Work on the notebooks

jupyter notebook

Acknowledgements

This work was supported by the High North Population Studies at UiT The Arctic University of Norway.