Measuring the organization of cardiac rhythms using the magnitude-squared coherence function

Area of Science:

• Biomedical Engineering
• Cardiology
• Signal Processing

Background:

• Assessing cardiac electrical activity organization is crucial for diagnosing arrhythmias.
• Existing methods may be limited in characterizing the complex dynamics of heart rhythms.

Purpose of the Study:

• To explore the utility of the magnitude-squared coherence (MSC) spectrum as a quantitative measure of cardiac electrical activity organization.
• To investigate the MSC spectrum's ability to differentiate between various cardiac rhythms.

Main Methods:

• Utilized bipolar electrograms from catheter or implantable cardioverter/defibrillator (ICD) electrodes.
• Calculated the magnitude-squared coherence (MSC) spectrum, a frequency-domain measure of linear signal relationships.
• Normalized the MSC spectrum to ensure insensitivity to signal gain differences.

Main Results:

• The MSC spectrum is a dimensionless, real-valued measure ranging from zero to unity.
• Zero MSC indicates no linear relationship between signals; unity indicates a linear, noise-free relationship.
• Demonstrated striking differences in MSC spectra between fibrillatory and non-fibrillatory cardiac rhythms.

Conclusions:

• The MSC spectrum is a robust and sensitive tool for evaluating the degree of organization in cardiac electrical activity.
• MSC analysis offers a promising method for distinguishing between different cardiac rhythm types, particularly fibrillation.