Abstract
Accurate identification of R-peaks is the basis of ECG correlation analysis. In this paper, we propose a method that first enhances the features of R-peaks using difference-square operations, and then locates R-peaks by threshold detection, slope judgment and backtracking search, where the threshold is a set of combined thresholds that are related to R peak amplitude, R-R interval and noise, respectively. The algorithm was tested on the MIT-BIH arrhythmia database, and the sensitivity Se = 99.59%, while the positive prediction rate +P = 99.71%. The method shows robustness with the addition of different noise levels. The experimental results show that the proposed algorithm reduces the false detection rate and increases the recognition rate, takes into account the real-time and anti-interference performance, and is suitable for the correlation analysis of ECG.
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References
Ari, S., Das, M.K., Anil, C.: ECG signal enhancement using S-Transform. Comput. Biol. Med. 43(6), 649–660 (2013)
Zhu, H., Dong, J.: An R-peak detection method based on peaks of Shannon energy envelope. Biomed. Sig. Process. Control 8, 466–474 (2013)
Pan, J., Tompkins, W.J.: A real-time QRS detection algorithm. IEEE Trans. Biomed. Eng. 32(3), 230–236 (1985)
Nguyen, T., et al.: Low resource complexity R-peak detection based on triangle template matching and moving average filter. Sensors 19(18), 3997 (2019)
Maciej, N., Miroslav, Z.: Wavelet-based unsupervised learning method for electrocardiogram suppression in surface electromyograms. Med. Eng. Phys. 38, 248–256 (2016)
Bouaziz, F., Boutana, D., Benidir, M.: Multiresolution wavelet-based QRS complex detection algorithm suited to several abnormal morphologies. IET Sig. Process 8, 774–782 (2014)
Arbateni, K., Bennia, A.: Sigmoidal radial basis function ANN for QRS complex detection. Neurocomputing 145, 438–450 (2014)
Moody, G.B., Mark, R.G.: The impact of the MIT-BIH Arrhythmia database. IEEE Eng. Med. Biol. 20(3), 45–50 (2001)
Tsai, Y.-R., Chang, Z.-Y., Huang, C.-W.: Time-domain multi-level R-peak detection algorithm for ECG signal processing. In: IEEE Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (2019)
Yazdani, S., Vesin, J.M.: Extraction of QRS fiducial points from the ECG using adaptive mathematical morphology. Digit. Sig. Process. 56, 100–109 (2016)
Moody, G.B., Muldrow, W.E., Mark, R.G.: A noise stress test for Arrhythmia detectors. Comput. Cardiol. 11, 381–384 (1984)
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Su, Z., Li, Y., Chen, K. (2022). A Robust R-Peaks Detection Algorithm of ECG Signals by Using Adaptive Combined Threshold. In: Jia, Y., Zhang, W., Fu, Y., Yu, Z., Zheng, S. (eds) Proceedings of 2021 Chinese Intelligent Systems Conference. Lecture Notes in Electrical Engineering, vol 804. Springer, Singapore. https://doi.org/10.1007/978-981-16-6324-6_20
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DOI: https://doi.org/10.1007/978-981-16-6324-6_20
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