Key result
A novel real-time QRS detection algorithm based on a moving average filter correctly detected over 99.5% of QRS complexes from a subset of the MIT-BIH arrhythmia database.
A novel, computationally simple moving average filter-based algorithm achieved >99.5% accuracy for real-time QRS detection on the MIT-BIH database.
May facilitate real-time ECG monitoring; leaves open prospective clinical validation before adoption.
This paper presents a novel real-time QRS detection algorithm designed based on a simple moving average filter. The proposed algorithm demands no redundant preprocessing step, thus allowing a simple architecture for its implementation as well as low computational cost. Algorithm performance was validated against a subset of the MIT-BIH arrhythmia database. Consequently, numerical results showed that the proposed algorithm correctly detected over 99.5% of the QRS complexes from the standard ECG database, implying it may be considered as a simple and reliable candidate of QRS detection algorithms.
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Chen et al. (2003) studied Arrhythmia. Moving average based filtering system for QRS detection was evaluated on QRS detection accuracy. A novel real-time QRS detection algorithm based on a moving average filter correctly detected over 99.5% of QRS complexes from a subset of the MIT-BIH arrhythmia database.
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