Analysis of aging effects on the arterial pulse contour using an artificial neural network

Age correlates both with the prevalence of cardiovascular diseases and with arterial pulse contour changes in healthy adults. If the effect of normal age-related changes can be better elucidated many of the increasingly popular methods of noninvasive pulse contour analysis could be made more reliable. In this paper, the predictability of age in 200 healthy adults is assessed using a radial basis function (RBF) network. The inputs are the complex coefficients of the Fourier transform of a single normalized pulse together with beat length, pulse and mean pressures, the harmonic at peak energy, and gender. Age is the output. Age predictability using different combinations of these components reveals that the first 27 harmonics contain aging information. Use of pulse pressure and harmonic of peak energy improved prediction, while mean pressure, beat length, and gender did not. These results suggest that age-related pulse contour changes in healthy adults are due to pulse pressure rather than absolute pressure, and energy shifts in the frequency distribution rather than changes in heart rate