Improvement of a FPGA-based Detection of QRS Complexes in ECG Signal using an Adaptive Windowing Strategy

Amina Habiboullah, Mehdi Terosiet, Aymeric Histace, Olivier Romain

Abstract

This paper presents an FPGA-based algorithm for automatic detection of QRS complexes in ECG signals, first step for the estimation of cardiac intervals. The proposed algorithm is divided into 3 parts : Filtering, Contrast Enhancement, and finally a Detection block based on an adaptive windowing and a thresholding of the enhanced data. The entire detection scheme was developed in accordance with embedding constraints and in the perspective of a real-time use. We evaluated the algorithm on manually annotated databases, such MIT-BIH Arrythmia and QT databases. The FPGA-based algorithm correctly detects 91,85 % percent of the QRS complexes, with a very limited ratio of false detection (only 5%) on standard databases, while for realtime records obtained from young subjects between 20 and 25 years, the sensitivity reaches 93,77 % with a false detection ratio of only 4 %. These results are in accordance with the most recent state-of-the-art off-line algorithms on the same database, and improves significantly FPGA-based ones that were tested on a limited number of ECG extracted from the MIT-BIH set of data only.

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Paper Citation


in Harvard Style

Habiboullah A., Terosiet M., Histace A. and Romain O. (2016). Improvement of a FPGA-based Detection of QRS Complexes in ECG Signal using an Adaptive Windowing Strategy . In Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: Smart-BIODEV, (BIOSTEC 2016) ISBN 978-989-758-170-0, pages 327-332. DOI: 10.5220/0005856403270332


in Bibtex Style

@conference{smart-biodev16,
author={Amina Habiboullah and Mehdi Terosiet and Aymeric Histace and Olivier Romain},
title={Improvement of a FPGA-based Detection of QRS Complexes in ECG Signal using an Adaptive Windowing Strategy},
booktitle={Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: Smart-BIODEV, (BIOSTEC 2016)},
year={2016},
pages={327-332},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005856403270332},
isbn={978-989-758-170-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 4: Smart-BIODEV, (BIOSTEC 2016)
TI - Improvement of a FPGA-based Detection of QRS Complexes in ECG Signal using an Adaptive Windowing Strategy
SN - 978-989-758-170-0
AU - Habiboullah A.
AU - Terosiet M.
AU - Histace A.
AU - Romain O.
PY - 2016
SP - 327
EP - 332
DO - 10.5220/0005856403270332