Person Identification

INTRODUCTION

This repository contains the implementation of the research paper titled "An integration of features for person identification based on the PQRST fragments of ECG signals". The paper presents a novel approach to identify the subjects using PQRST fragments of the electrocardiogram (ECG) signal¹. The method is based on identification the system which has three principal steps, namely preprocessing, features extraction, and classification.

The code in this repository is organized into.

• src : Contains all the codes files, files have been named based on its functions.
• Features : Features extarcated from the ECG signal are availale in this directory.

To run the code, install neccessary dependencies.

Note : Model Training is not done on MIT_BIH features file.

CITATION AND REFERENCE

If you use any of resources from the paper in your own research, please cite the paper using the following citation:

PLAIN TEXT

Hamza, S., Ayed, Y.B. An integration of features for person identification based on the PQRST fragments of ECG signals. SIViP 16, 2037–2043 (2022). https://doi.org/10.1007/s11760-022-02165-8

Bib TeX

@article{hamza2022integration,
  title={An integration of features for person identification based on the PQRST fragments of ECG signals},
  author={Hamza, Sihem and Ayed, Yassine Ben},
  journal={Signal, Image and Video Processing},
  volume={16},
  number={8},
  pages={2037--2043},
  year={2022},
  publisher={Springer}
}

If you use any of the code or resources from this repository in your own research, please also cite the GitHub repository.

If you have any questions or encounter any issues, please feel free to open an issue on this repository or contact the repository authors. We hope that this implementation will be useful for other researchers in the field.

Footnotes

1. An integration of features for person identification based on the PQRST fragments of ECG signals. ↩