Why the study?
Does a nonlinear wave separation method improve the accuracy of determining forward and backward arterial pressure waves compared to a classical linear method?
Does a nonlinear wave separation method improve the accuracy of determining forward and backward arterial pressure waves compared to a classical linear method?
A new nonlinear method for separating arterial pressure waves is more accurate than the classical linear method, but the difference (5-10%) is clinically negligible, supporting the continued use of the simpler linear method.
Linear methods suffice for most clinical arterial wave analysis; leaves open nonlinear value in high-precision research or specific cohorts.
A new separation technique has been developed to determine the forward and backward running arterial pressure wave components. It takes into account friction as well as nonlinear effects due to convective acceleration and to the pressure dependence of the arterial compliance. The new method is a combination of two methods treating friction and nonlinearities separately. The method requires the measurements of pressure and flow at one location as well as the knowledge of the area-pressure relationship. The validity of the method was tested by a simulation experiment in which the forward and backward waves were known a priori. It was shown that the new method is significantly more accurate in the predictions of the forward and backward waves when compared to the classical method assuming linearity and no dissipation. The new wave separation method was also applied to simulated aortic waves for (a) a healthy subject and (b) a subject with decreased compliance. Comparison with the classical linear method showed that neglecting nonlinearities leads to an overestimation of the forward and backward pressure wave amplitudes. The errors, however, were in the order of 5 to 10 percent. We concluded that, for most clinical purposes, the improvement using the nonlinear method is of the same magnitude as experimental errors, and thus the linear method would suffice.
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Pythoud et al. (1996) studied this question.
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