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Multi-parameters study of detecting cardiac status with nonlinear dynamics

Cardiac state activity has rich information, electrocardiac activity especially. It is controlled by many factors, such as the maintenance of states, the modification of states, and the execution of behavioral responses, and relates to non-linear dynamics system. We have been spending major efforts by investigation to study several independent methods of non-linear dynamics to detect heart states and the results were good. The parameters we selected were two quantity indices of dispersed-dot plot that is the area of plot (SQ) and long-axis (LA), that have certain idiosyncrasy with different heart diseases. The SQ and LA of healthy subjects had the biggest among all heart states, and different disease got different and smaller parameter shape. Fractal dimension had the similar results as above and could make known one's healthy level or latent potentialities. The Lyapunov exponent showed that patients with different diseases were different from each other, which can distinguish the bioregulative capacity of people, healthy human changes and losing a lot of information content in the early morning and patients being not present. The mutual information (MI) related the healthy level of the heart, which was varied while the heart pathologically changed, and MI became large. This new approach of detecting multi-parameters from electrocardiac information may be useful for clinical application and diagnosis.