Nonlinear dynamics analysis of electrocardiograms for detection of coronary artery disease

A computerized approach of nonlinear dynamics analysis of electrocardiogram (ECG) signals was applied for the detection of coronary artery disease (CAD). The proposed nonlinear dynamics descriptors were derived from 12-lead rest ECG data, and evaluated by originally developed computer software.Fluctuations of potentials of ECG leads that occur during the period of 20 ms with a magnitude of 5–20 μV were significantly less beat-to-beat predictable in ischemic versus non-ischemic patients. The well-known nonlinear dynamics descriptors, recurrences percentage, mutual information, fractal dimension, and a new descriptor, next embedding dimension error, were good quantitative descriptors of fluctuations. They were significantly different (