Problems and limitations of ECG baseline estimation and removal using a cubic spline technique during exercise ECG testing: recommendations for proper implementation.

One common variety of exercise-induced artifact is baseline wander resulting from movement, respiration, and poor electrode contact. Although filters can be designed to remove much of this baseline variation, they will distort the low-frequency components of the ECG complex, such as the TP-segment, the PR-segment, and, most problematically, the ST-segment. The ST-segment is the most diagnostically relevant measure of the ECG taken during exercise. While linear baseline interpolation and removal may be adequate at lower heart rates, they also will introduce significant distortions. This is particularly evident when excessive nonlinear wander is present, as seen at higher heart rates and respiration rates. A nonlinear, third-order, polynomial estimator of baseline wander, known as the cubic spline, has been used for nearly 15 years. It is a very robust technique applied to exercise ECG recordings. Since the cubic spline is not a filter and use an a priori knowledge of the shape of the ECG signal, it estimates the true baseline and avoids distortion better. The more common implementations of this technique use relatively short ECG recordings. With the advent of increasing power in computerized ECG systems, the implementation of the cubic spline algorithm for removing baseline wander in continuous, longer-duration ECG records and in real-time processing is being attempted. However, the correct application of the cubic spline to continuous recordings is not straightforward and involves a number of previously unforeseen difficulties. The accuracy and resolution of both floating point and integer operations is critical during long-term application of the cubic spline function.(ABSTRACT TRUNCATED AT 250 WORDS)