Analysis of heart rate variability on a massively parallel processor

The K₂ entropy, and the correlation dimension are commonly used measures of chaotic activity in complex dynamic systems. The design and implementation of a massively parallel algorithm on the MasPar MP-2 for the computation of K₂ entropy and the correlation dimension is presented. The algorithm is used to compute the K₂ entropy and correlation dimension of experimental heart rate data. Experimental results on canine subjects support the claim that K₂ entropy and the correlation dimension can be used as a measure of the heart rate variability and the level of chaos present in the nonlinear dynamics underlying the heart rate data. The parallel algorithm has potential for use as a tool for cardiac health assessment and diagnosis of certain cardiac ailments