An algorithm for phase-space detection of the P characteristic points.

Area of Science:

• Biomedical Engineering
• Signal Processing
• Cardiology

Background:

• Electrocardiogram (ECG) analysis is crucial for diagnosing cardiac conditions.
• Accurate detection of P-wave characteristic points is essential for ECG interpretation.
• Existing methods face challenges with noise and signal variability.

Purpose of the Study:

• To introduce a new algorithm for detecting P-wave characteristic points in multi-lead ECG signals.
• To enhance the robustness of P-wave detection against various signal interferences.
• To provide a reliable tool for automated ECG analysis.

Main Methods:

• The algorithm employs embedding phase space to represent ECG signals.
• Similar ECG morphologies are mapped to proximate points in the phase space using a distance measure.
• The method focuses on detecting onset, peak, and end points of the P-wave.

Main Results:

• The algorithm demonstrates robustness against different characteristic point selections.
• It effectively handles morphology changes, baseline oscillations, and high-frequency noise.
• Successful validation was achieved using both simulated and real ECG data.

Conclusions:

• The proposed embedding phase space algorithm offers a robust and accurate method for P-wave detection.
• This technique has significant potential for improving automated ECG interpretation systems.
• The algorithm's resilience to common ECG signal artifacts makes it clinically relevant.