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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.