Detection and measurement of the P-wave and T-wave during exercise testing using combined heuristic and statistical...

Area of Science:

• Cardiology
• Biomedical Engineering
• Signal Processing

Background:

• Detecting P-wave and T-wave components in electrocardiogram (ECG) analysis is challenging, especially during exercise testing due to T-P wave fusion at higher heart rates.
• Traditional computerized ECG analysis often avoids or struggles with accurate measurement of these crucial waveform components.

Purpose of the Study:

• To develop and validate an advanced ECG analysis program capable of reliably detecting, measuring, and tracking P-wave and T-wave components during exercise testing.
• To overcome the limitations of visual detection and existing automated methods, particularly in the presence of T-P fusion.

Main Methods:

• Integration of advanced pattern recognition, statistical measurements, and heuristic decision-making logic within the ECG Analysis program.
• Creation of a comprehensive database for consecutive ECG records, enabling comparison of current measurements with historical data.
• Implementation of an expert system approach that continuously updates and adapts to individual ECG morphologies throughout the exercise test.

Main Results:

• The developed ECG Analysis program demonstrates reliable detection and measurement of P-wave and T-wave components during exercise testing, exceeding the accuracy of experienced human readers.
• The system successfully tracks these components even when T-P fusion occurs at high heart rates.
• Preliminary efforts show promise in separating, extracting, and normalizing fused P-waves and T-waves for enhanced analysis.

Conclusions:

• The advanced ECG analysis program offers a robust solution for accurate P-wave and T-wave detection and measurement during exercise stress tests.
• This expert system approach provides a dynamic and adaptive method for ECG interpretation, improving diagnostic capabilities.
• Further research into wave separation during fusion may yield deeper insights into cardiac electrophysiology at high heart rates.