Variability maps of body surface ECG in normal subjects

Area of Science:

• Cardiology
• Biomedical Engineering
• Signal Processing

Background:

• Quantifying electrocardiogram (ECG) signal variability on the body surface is essential for diagnosing cardiac conditions.
• Understanding normal ECG fluctuations is key to identifying pathological deviations.
• Previous methods lacked comprehensive analysis of spatial and temporal ECG variability.

Purpose of the Study:

• To develop and validate a method for quantifying QRS complex fluctuations on the unrolled thoracic surface.
• To establish similarity measures for serial ECG comparisons in healthy subjects.
• To map the topology of normal ECG variability across the body surface.

Main Methods:

• Utilized 32-lead ECG recordings and body surface maps from seven healthy males.
• Employed correlation and Root Mean Square (RMS)-difference as similarity metrics.
• Performed serial comparisons in both time-signal and 2D map domains, including isointegral maps.

Main Results:

• High average time-signal correlation (0.9717) and low RMS-difference (57.8 microV) were observed between recordings on different days.
• 2D map comparisons yielded similar results (correlation 0.9696, RMS-difference 68.9 microV).
• Isointegral map comparisons showed even higher correlations (0.98) and lower RMS-differences (3.453 microV s).

Conclusions:

• Correlation and RMS-difference are pertinent measures for assessing ECG time-signal and map similarity.
• The study identified normal ranges of ECG variability on the body surface.
• These findings provide a basis for detecting cardiac pathologies by highlighting deviations from normal ECG patterns.