Nonlinear wavelet and wavelet packet denoising of electrocardiogram signal.

The performance of different wavelet- and wavelet packet-based methods for removing simulated noise was studied using an electrocardiogram (ECG) signal. A non-linear denoising approach was investigated by applying soft and hard thresholding methods, in which thresholds were chosen using four different methods. Coiflet wavelet and wavelet packet functions were used to build up the dyadic wavelet and optimized wavelet packet decompositions. This study involves the quantitative comparison of different denoising approaches by means of optimized error measures and visual inspection of the denoised ECG and the error signal. The localization of the denoising error within the cardiac cycle was studied by visual inspection of the denoised signal and extracting the error measures during the QRS-complex. The results showed that wavelet denoising approaches were generally more efficient than wavelet packet approaches in all cases, but with Heuristic Sure threshold selection rule as hard thresholding for white noises was used. Denoising errors tend to concentrate within the QRS-area when the wavelet approach was employed. Moreover, soft and hard non-linearities showed different balances in denoising the high-frequency parts of an ECG.

Using simulated noise to define optimal QT intervals for computer analysis of ambulatory ECG.

The ambulatory electrocardiogram (ECG) is an important medical tool, not only for diagnosis of adverse cardiac events, but also to predict the risk of such events occurring. The 24-hour ambulatory ECG has certain problems and drawbacks because the signal is corrupted by noise from various sources and also several other conditions which may alter the ECG morphology. We have developed a Windows based program for the computer analysis of ambulatory ECG which attempts to address these problems. The software includes options for importing ECG data, different methods of waveform analysis, data-viewing, and exporting the extracted time series. In addition, the modular structure allows for flexible maintenance and expansion of the software. The ECG was recorded using a Holter device and oversampled to enhance the fidelity of the low sampling rate of the ambulatory ECG. The influence of different sampling rates on the interval variability were studied. The noise sensitivity of the implemented algorithm was tested with several types of simulated noise and the precision of the interval measurement was reported with SD values. Our simulations showed that, in most of the cases, defining the end of QT interval at the maximum of the T wave gave the most precise measurement. The definition of the onset of the ventricular repolarization duration is most precisely made on the maximum or descending maximal slope of the R wave. We also analyzed some examples of time series from patients using power spectrum estimates in order to validate the low level QT interval variability.

Simultaneous invasive and noninvasive evaluations of baroreflex sensitivity with bolus phenylephrine technique.

Estimation of baroreflex sensitivity (BRS) is receiving increasing attention in clinical and experimental cardiology. Until recently, in most studies BRS has been assessed on the basis of invasive blood pressure measurement, which limits its use in large-scale studies and in clinical practice. The development of continuous noninvasive blood pressure monitoring has made it possible to assess BRS noninvasively. We compared central invasive and peripheral noninvasive techniques in the assessment of BRS during cardiac catheterization in 40 patients with possible coronary artery disease. The correlation between noninvasive and invasive BRS was high (r = 0.92; p < 0.001). However, the noninvasive method resulted in significantly higher BRS values than did the invasive method (7.1 +/- 6.5 msec/mm Hg vs 5.1 +/- 4.3 msec/mm Hg, respectively; p < 0.001) because of the smaller increase in systolic blood pressure after phenylephrine injection by the noninvasive technique than by the invasive technique (18.9 +/- 6.8 mm Hg vs 25.2 +/- 7.8 mm Hg, respectively; p < 0.01). The difference between noninvasive and invasive BRS correlated positively with invasive BRS (r = 0.54; p < 0.001) and inversely with age (r = -0.39; p < 0.01) and resting systolic blood pressure (r = -0.30, p < 0.05). A noninvasive BRS value of < 4.0 ms/mm Hg showed a sensitivity of 94%, a specificity of 91%, and an accuracy of 93% in identifying cases of reduced invasive BRS (< 3.0 msec/mm Hg). Our findings encourage the use of finger-cuff method in the assessment of BRS. However, noninvasive BRS values were slightly but significantly higher than invasive BRS values, a difference that should be taken into account when BRS is measured by the noninvasive approach.