Improvement of a FPGA-Based Detection of QRS Complexes in ECG Signal Using An Adaptive Windowing Strategy
Résumé
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.