[A new method using the technique of cubic spline interpolation to remove baseline wander]

Area of Science:

• Biomedical Engineering
• Signal Processing
• Cardiovascular Technology

Context:

• Baseline wander in electrocardiogram (ECG) signals is a common artifact that can obscure diagnostic information.
• Current methods for baseline wander correction often rely on P-R intervals, which are susceptible to noise and irregular heart rhythms.
• Accurate baseline estimation is crucial for reliable ECG interpretation and automated analysis.

Purpose:

• To develop a novel and robust method for determining fiducial points for baseline wander correction in ECG signals.
• To overcome the limitations of P-R interval-based fiducial point detection in noisy or irregular ECG recordings.
• To improve the accuracy and reliability of ECG baseline wander correction.

Summary:

• A new method identifies fiducial points using the high-frequency characteristics of the QRS complex.
• The technique involves approximate baseline correction with a FIR filter, followed by R-peak detection and amplitude analysis.
• Fiducial points are then connected using cubic spline interpolation to estimate a continuous baseline, demonstrating superior performance compared to existing methods.

Impact:

• Provides a more accurate and robust approach to ECG baseline wander correction, especially in challenging signal conditions.
• Enhances the quality of ECG data, leading to improved diagnostic accuracy and potentially better patient outcomes.
• Offers a valuable alternative for researchers and clinicians dealing with noisy or artifact-ridden ECG signals.