WSEAS Transactions on Computers


Print ISSN: 1109-2750
E-ISSN: 2224-2872

Volume 16, 2017

Notice: As of 2014 and for the forthcoming years, the publication frequency/periodicity of WSEAS Journals is adapted to the 'continuously updated' model. What this means is that instead of being separated into issues, new papers will be added on a continuous basis, allowing a more regular flow and shorter publication times. The papers will appear in reverse order, therefore the most recent one will be on top.



A Low-complexity QRS Detection Algorithm Based on Morphological Analysis of the QRS Complex

AUTHORS: Li Lu, Xiangyan Kong, Kang Yang, Hua Chen, Ruihu Yang

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ABSTRACT: QRS detection in the magnetocardiogram (MCG) and electrocardiogram (ECG) signals is very crucial as the first step for evaluating the cardiac function. Unlike most of the published algorithms which are aimed at increasing the detection accuracy by using complex signal-processing techniques, we propose a new, low-complexity QRS detection algorithm based on morphological analysis of the QRS complex. The algorithm does not need to remove the baseline wander, and the R waves can be quickly detected by the wave steepness function. The performance of the proposed algorithm was evaluated on the MIT-BIH arrhythmia database and MCG data recorded by the multi-channel MCG system. The sensitivity (SE) and positive prediction (+P) for MIT-BIH database were 99.69% and 99.87%, respectively. Also, the accuracy of 97.22% is achieved for MCG data. Compared to other published results, the processing time of one hour ECG data was reduced to 0.187s. The lower computational time makes the proposed method can be used in portable devices, for example, a Smartphone.

KEYWORDS: Magnetocardiogram; wave steepness function; Morphological analysis; QRS complex

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WSEAS Transactions on Computers, ISSN / E-ISSN: 1109-2750 / 2224-2872, Volume 16, 2017, Art. #31, pp. 269-277


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