Event_based_gQRS/c633dd1f6833master
README.md
Event based gQRS
In this repository is possible to find the source code for the event-based gQRS algorithm for R peak detection in ECG signals. The python demonstrative version, C version implemented on the PULP platform, Mr.Wolf, and the tools necessaries to extract and re-sample the data can be found here.
Getting Started
Prerequisites
- Python version:
- Jupyter-notebook
- Python 3.6.x
- Numpy
- Pandas
- Matplotlib
- wfdb
- tqdm
- C version:
- gCC
- Installing and Running
- Create a data folder on the root direcotry of this project, this will be the directory of your RAW data and the output directory.
- Insert your dataset in the MIT-BIH database format (.dat and .hea files) in a subfolder, for example, "dataRaw".
- The database used for developing and testing this algorithm can be found at MIT-BIH Arrythmia Database
- Move in the "data_parsing" folder and lunch ECG_lvlCrossing.py
python3 ECG_lvlCrossing.py -i ../data/dataRaw -o ../data/dataOut --threshold 100
This script will extract and resample with a threshold "--threshold" all the file in the MIT-BIH format found in the direcotry passed by the "-i" argument and output the results in the folder passed with "-o"
(Note: is possible also to pass the path of a single file as input.)
- Python version:
- Run the jupiter notebook contained in the "python_gQRS" folder.
C version:
Important note: This is not a plain C-99 project. this project was developed for the PULP platform "Mr. Wolf"
- Move in the "data_parsing" folder and lunch "makeDataHeader.py"
python3 makeDataHeader.py -s ../data/dataOut/selectedFile
This will create automatically the header containing the data from file "selectedFile" to be used by the C code
- Move to the "C_gQRS" folder
- follow the steps at PULP platform SDK and toolchain.
- Execute:
make clean all run
This will start to run the simulation for the selected file multiple time, measuring several parameters of the simulation and returning an overview of the score-results and the performance-results
Built With
Authors
- Silvio Zanoli - ESL Lab
- Tomas Teijeiro - ESL Lab
- Fabio Montagna - University of Bologna
License
This project is licensed under the GPL License - see the <u>LICENSE.txt</u> file for details
Acknowledgments
Thanks to:
- Prof. Dr. David Atienza Alonso
- The Human Brain Project (HBP) SGA2 (GA No. 785907)
- The ESL Lab