Abstract
QRS detection is needed for electrocardiogram (ECG) signal analysis, including the Heart Rate Variability (HRV) analysis, which is the physiological phenomenon of variation of the time intervals between two consecutive heartbeats. R is the point corresponding to the peak of a QRS complex of ECG waves. RR-interval is defined as the interval between two successive Rs. We proposed an algorithm to acquire RR-interval based on a level-4 Stationary Wavelet Transform (SWT) to decompose ECG signal followed by an adaptive thresholding algorithm to separate QRS complex from other unwanted signals. Daubechies filter is chosen as the mother wavelet, because its shape of the scaling function resembles a QRS complex. The proposed algorithm is simulated by MATLAB, where 48 files from MIT-BIH arrhythmia database are used as benchmarks to verify the algorithm. Simulation results show 99.64% of sensitivity and 99.48% of positive predictivities.
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References
Bayasi N, Saleh N, Mohammad B, Ismail M (2014) 65-nm ASIC implementation of QRS detector based on Pan and Tompkins algorithm. In: 10th International conference on innovations in information technology (IIT). Al Ain, United Arab Emirates, 9–11 Nov 2014, pp 84–87
Zhang X, Lian Y (2014) A 300-mV 220-nW event-driven ADC with real-time QRS detection for wearable ECG sensors. IEEE Trans Biomed Circ Syst 8(6):834–843
Tang X, Hu Q, Tang W (2018) A real-time QRS detection system with PR/RT interval and ST segment measurements for wearable ECG sensors using parallel delta modulators. IEEE Trans Biomed Circ Syst 12(4):751–761
Mallat S (2009) A wavelet tour of signal processing. Academic, New York
Mallat S (1989) Multifrequency channel decompositions of images and wavelet models. IEEE Trans Acoust Speech Sig Process 37(12):2091–2110
Nason G, Silverman B (1995) The stationary wavelet transform and some statistical applications. University of Bristol
Merah M, Abdelmalik TA, Larbi BH (2016) R-peaks detection based on stationary wavelet transform. Comput Methods Programs Biomed 121(3):149–160
Daubechies I (1988) Orthonormal bases of compactly supported wavelets, communications on pure and applied mathematics, vol XLI, pp 909–996
Liu C-L (2010): A tutorial of the wavelet transform
Thakor NV, Webster JG, Tompkins W (1983) Optimal QRS detector. Med Biol Eng Comput 21(3):343–350
Webster JG (2010) Medical instrumentation application and design. Wiley, New York
Physionet. PhysioBank ATM homepage. https://www.physionet.org/cgi-bin/atm/ATM. Last accessed on 23 Sept 2018
Ravanshad N, Rezaee-Dehsorkh H (2017) An event-based ECG-monitoring and QRS-detection system based on level-crossing sampling. In: 2017 Iranian conference on electrical engineering (ICEE), Tehran, pp 302–307
Acknowledgements
This research was partially supported by Ministry of Science and Technology under grant MOST 106-2221-E-110-058-, 107-2218-E-110-016-, and 107-2218-E-110-004-.
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Rif’an, M., Rieger, R., Wang, CC. (2020). Accurate RR-Interval Detection with Daubechies Filtering and Adaptive Thresholding. In: Zakaria, Z., Ahmad, R. (eds) Advances in Electronics Engineering. Lecture Notes in Electrical Engineering, vol 619. Springer, Singapore. https://doi.org/10.1007/978-981-15-1289-6_6
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DOI: https://doi.org/10.1007/978-981-15-1289-6_6
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