Diagnosis of functional heart disease and heart disease prognostication with emphasis on the multifractal alpha, the Levy flight analysis and the key discrete wavelet smoothing.

1-d Multifractal Analysis (MFA) of Human Heart Beats

Novel Assessment of Cardiovascular Risk utilizing 1-d Multifractal Analysis (MFA) of Human Heart Beats

Application: Diagnosis of functional heart disease and heart disease prognostication with emphasis on the multifractal alpha, the Levy flight analysis and the key discrete wavelet smoothing.

The results of this research demonstrate the enormous potential of multifractal EKG analysis in the diagnostic and prognostication of chronic heart failure. Researchers have emphasized the multifractal alpha, the Levy flight analysis and the key discrete wavelet smoothing. Future studies will address the Pathology fractal reference.

Many of the 1 million cardiovascular disease patients that die each year die from sudden death related to arrhythmia. There is an acute need for accurate prediction of patients at high risk for death, especially arrythmia related to sudden death. Researchers have developed a novel approach toward the analysis of normal and abnormal human heart function, using an extension of existing fractal methods of analysis, called multifractal analysis (MFA). This novel method is software- based. MFA detects the multifractal nature of the human heartbeat and can distinguish between normal and abnormal utilizing a number of methods. Researchers have perfected a new method of removing arrythmias from the EKG RR beat interval signals before fractal analysis, which will identify many of the arrythmia patients at risk for sudden death. This invention has been extensively tested in patients with known multifractal generating program, showing excellent agreement with theory for the Holder range of 0.5 - 0.4. These results are in agreement with simpler monofractal methods.

This state of the art pathologic histomorphometry, MFA, is a significant improvement in pathologic image analysis, providing 10X more information than other pattern recognition methods. One-dimensional MFA developed by this research may be ideally suited for digital pathologic image analysis, as it is less computationally intensive than 2-d MFA analysis.

Additional applications include 1) prediction of arrythmia induced sudden death risk, 2) response to antiarrythmic drug therapy, and 3) pathologic histomorphometry applications.

Reference: "Multifractal wavelet analysis of human heartbeat predicts cardiovascular dysfunction with high sensitivity and specificity" abstract submitted to ACA copy available on request.

02-01

Preclinical

Patent Status: U.S. Patent #6,993,377 issued 1/31/06

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