Abstract
A new real-time detection algorithm, which combines merits of the real-time detection algorithm proposed by Pan and the QRS detection algorithm based on Hilbert transform, is proposed to improve detection accuracy of ECG R-wave. The original data are firstly processed by using of Hilbert transform to improve the signal to noise ratio (SNR). Considering the quasi-periodic characteristics of the ECG, the adaptive threshold designed in Pan's real-time detection algorithm is adopted to execute threshold detection for ECG waveform with small range. In this paper, the MIT/BIH Arrhythmia Database are used to verify the effectiveness of the proposed algorithm, and the results show an average R-wave detection error rate of 0.63%. Comparing with results obtained in other literatures, implementation of the algorithm is significantly simplified while the detection accuracy is favorable.
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