A computational approach to predict pulse transit time variations during postural change.

The human autonomic nervous system modulates blood pressure (BP) and heart rate in order to maintain homeostasis. Present techniques that monitor BP may cause discomforts to children. Pulse transit time change (DeltaPTT) is known to be inversely correlated to BP change. In this study, a mathematical model using only a few empirical parameters and the measured lower limb vascular path length is introduced to estimate DeltaPTT when a different posture is adopted. To assess the reliability of the model, 23 healthy children aged 8.4 +/- 2.3 years were recruited to adopt the sitting and supine position at discrete intervals. PTT measurements were obtained from their toe with respect to an ECG for both postures. The results showed that there was significant correlation between the model and measured DeltaPTT (P < 0.05; R(2) = 0.813). The findings herein suggest that this simple yet practical model can have the accuracy to estimate the DeltaPTT value. Moreover, it does not require the use of an ECG or pulse oximeter in its computation. Hence, it can provide a rapid prediction before a child adopts a postural change. This may be potentially useful for detection of children with vascular abnormalities at their lower limbs.