Authors:
Amina Habiboullah
;
Mehdi Terosiet
;
Aymeric Histace
and
Olivier Romain
Affiliation:
University of Cergy-Pontoise and CNRS, France
Keyword(s):
ECG, QRS Detection, Embedded Processing, FPGA.
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 impr
oves 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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