Optimizing the Impact of Resampling on QRS Detection

QRS detection is an essential activity performed on the electrocardiogram signal for finding heartbeat features. Even though there is already a lot of literature on QRS detection, we set a research question to find the dependence of QRS detection performance on the sampling frequency, and, if possible, to find a QRS detector that will be highly efficient at different sampling rates. Our synthesis technique aims to find the optimal value of the threshold parameters that define if the detected peak is artifact, noise or real QRS peak. In addition, we conducted experimental research to find the dependence and estimate the optimal threshold values for the best QRS detection performance. Our approach results with increased QRS detection performance on the original sampling frequency by improving the original Hamilton algorithm. We tested with the MIT-BIH Arrhythmia database. Lastly, QRS detection sensitivity and positive predictive rate are used to evaluate the performance of the algorithm.

[1]  G.B. Moody,et al.  The impact of the MIT-BIH Arrhythmia Database , 2001, IEEE Engineering in Medicine and Biology Magazine.

[2]  Marjan Gusev,et al.  Amplitude Rescaling Influence on QRS Detection , 2018, ICT Innovations.

[3]  Jeffrey M. Hausdorff,et al.  Physionet: Components of a New Research Resource for Complex Physiologic Signals". Circu-lation Vol , 2000 .

[4]  Harry Nyquist.  Certain Topics in Telegraph Transmission Theory , 1928 .

[5]  Willis J. Tompkins,et al.  Quantitative Investigation of QRS Detection Rules Using the MIT/BIH Arrhythmia Database , 1986, IEEE Transactions on Biomedical Engineering.

[6]  O. Pahlm,et al.  Software QRS detection in ambulatory monitoring — a review , 1984, Medical and Biological Engineering and Computing.

[7]  Willis J. Tompkins,et al.  A Real-Time QRS Detection Algorithm , 1985, IEEE Transactions on Biomedical Engineering.

[8]  Marjan Gusev,et al.  ECGalert: A Heart Attack Alerting System , 2017, ICT Innovations.

[9]  Marjan Gusev,et al.  Analysis of sampling frequency and resolution in ECG signals , 2017, 2017 25th Telecommunication Forum (TELFOR).

[10]  J. Thayer,et al.  A careful look at ECG sampling frequency and R-peak interpolation on short-term measures of heart rate variability , 2015, Physiological measurement.

[11]  G. Berntson,et al.  An approach to artifact identification: application to heart period data. , 1990, Psychophysiology.

[12]  G. Breithardt,et al.  Heart rate variability: standards of measurement, physiological interpretation and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. , 1996 .

[13]  T. Ziemssen,et al.  Influence of ECG Sampling Frequency on Spectral Analysis of RR Intervals and Baroreflex Sensitivity Using the EUROBAVAR Data set , 2008, Journal of Clinical Monitoring and Computing.

[14]  A. Malliani,et al.  Heart rate variability. Standards of measurement, physiological interpretation, and clinical use , 1996 .