A New Spectrum Driven Index for the Assessment of ECG Signal Quality

In this paper, a new simple index has been introduced for the assessment of electrocardiography (ECG) signal quality. In the proposed method, first, the initial spectrum of the ECG is derived by applying synchrosqueezed wavelet transform (SSWT). Then, the main frequency rhythm of heart rate with maximum-energy embedded in the spectrum of the ECG signal is reconstructed using time-frequency ridge estimation algorithm. The ridge is subjected to the inverse SSW and SSW subsequently to reconstruct a clear spectrum corresponding to the main heart rhythm. Subtracting it from the initial spectrum, the resulting differential spectrum is converted to a single time-series by simply summing all the energy levels at each time-point. It has been shown that the derived time-series is proportional to the quality of ECG signal in terms of preserving its physiological features. The results of this research provide a profound basis for signal quality assessment of both ECG and photoplethysmography (PPG) signals under various noisy conditions and abnormal heart rate.

[1]  Yefei Zhang,et al.  SQI Quality Evaluation Mechanism of Single-Lead ECG Signal Based on Simple Heuristic Fusion and Fuzzy Comprehensive Evaluation , 2018, Front. Physiol..

[2]  Qifei Zhang,et al.  A Cascaded Convolutional Neural Network for Assessing Signal Quality of Dynamic ECG , 2019, Comput. Math. Methods Medicine.

[3]  Negin Yaghmaie,et al.  Dynamic signal quality index for electrocardiograms , 2018, Physiological measurement.

[4]  G D Clifford,et al.  Signal quality indices and data fusion for determining clinical acceptability of electrocardiograms , 2012, Physiological measurement.

[5]  Qiao Li,et al.  ECG Signal Quality During Arrhythmia and Its Application to False Alarm Reduction , 2013, IEEE Transactions on Biomedical Engineering.

[6]  Aleš Procházka,et al.  Multi-Class Sleep Stage Analysis and AdaptivePattern Recognition , 2018 .

[7]  Shoushui Wei,et al.  Signal Quality Index-Based Two-Step Method for Heart Rate Estimation by Combining Electrocardiogram and Arterial Blood Pressure Signals , 2018, Journal of Medical Imaging and Health Informatics.

[8]  I. Daubechies,et al.  Synchrosqueezed wavelet transforms: An empirical mode decomposition-like tool , 2011 .

[9]  Ales Procházka,et al.  Detection of Sleep Apnea/hypopnea Events Using Synchrosqueezed Wavelet Transform , 2019, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[10]  D. Strauss,et al.  Assessing ECG signal quality indices to discriminate ECGs with artefacts from pathologically different arrhythmic ECGs , 2016, Physiological measurement.