Biomedical subjects

K W Fulton

Publications and source records attributed to K W Fulton.

2 recordsLinked to original sources

PubMed1992

Slope filtered pointwise correlation dimension algorithm and its evaluation with prefibrillation heart rate data.

Various studies have shown that a low variability in heart rate is associated with increased risk of ventricular fibrillation. Low chaotic (correlation) dimension in the heart rate also appears to predict fibrillation risk. However, these results have been based on intergroup comparisons and have not been found useful for predicting when a patient may fibrillate with any degree of sensitivity, specificity, or temporal accuracy. There are two primary limitations in using dimensional analysis to predict imminent fibrillation. The first is that the standard algorithms (for correlation dimension) assume stationarity of the system. The second limitation is that these algorithms require 10,000-50,000 data points to achieve good accuracy. Thus, even if stationarity were not an issue, there would be a lag of 2.4-12 hours to warn of impending fibrillation. An algorithm has been developed to calculate an accurate pointwise correlation dimension of heart rate data. The slope filtered pointwise correlation dimension algorithm requires as few as 1,000 points of data. Using this algorithm, it was found that the correlation dimension dropped from 2.50 +/- 0.81 to 1.07 +/- 0.18 in the minute before fibrillation in conscious pigs with an occluded coronary artery. In clinical studies, Holter tapes from patients that had suffered fatal fibrillation were also analyzed along with healthy controls and nonfibrillation ventricular patients. The fibrillation patients all had excursions of low dimension (less than 1.5), while the majority of the others did not. In the minutes before fibrillation, the correlation dimension dropped to a steady range of 0.8-1.3. Drops in the slope filtered pointwise correlation dimension appear to predict fibrillation in animals and patients.

Algorithms↗

PubMed1991

Correlation dimension of heartbeat intervals is reduced in conscious pigs by myocardial ischemia.

A reduced standard deviation of RR intervals (SDRR) predicts increased mortality in groups of survivors of myocardial infarction. Like SDRR, the correlation dimension (D2) describes variation within a sampled time series, but uniquely it reveals 1) the epoch's geometric structure and 2) the degrees of freedom of the generator. These unique features may be more sensitive predictors of mortality than SDRR. We developed a new algorithm for estimating D2 (i.e., the "point-D2"), tested it with known data, and found that it had greater accuracy for finite data than other published algorithms. Analysis of RR intervals from eight conscious pigs undergoing acute occlusion of the left anterior descending coronary artery revealed a drop in the point-D2 from a control mean and standard deviation of 2.50 +/- 0.81 to 1.58 +/- 0.64 during the first minute of ischemia (p less than 0.01) and to 1.07 +/- 0.18 during the last minute preceding ventricular fibrillation (p less than 0.01). Partial occlusions (50-90% reduction of coronary blood flow) evoked point-D2 reductions only 25-30% of control (p less than 0.01). The point-D2 means were correlated between pigs with the magnitude of the respiratory sinus arrhythmia (p less than 0.01), but during ischemia this correlation was replaced by one between the standard deviation of the point-D2s and SDRRs. Because the simultaneous reduction in the mean point-D2 and its standard deviation to 1.07 +/- 0.18 occurred in every case, was unique to the few minutes preceding ventricular fibrillation, and never reached these low values during other conditions in which it was reduced, we conclude that the point-D2 may be an accurate prospective predictor of mortality within the individual subject.

Algorithms↗