ABSTRACT
Background: Repetitive experiences of certain stresses evoke feedforward cardiovascular responses via central command (CC)--central signals from the higher brain. However, it is unclear whether the anticipatory cardiovascular responses before pain stimulation occur after repetitive pain experiences and how nitrous oxide/oxygen inhalation (N2O), a sedative widely used in dentistry, affects the responses. We tested the hypothesis that the repetitive cold pressor test (CPT) alters the anticipatory cardiovascular responses, which are attenuated by N2O. Materials and methods: Beat-to-beat systolic (SBP) and diastolic blood pressure (DBP), heart rate (HR), and finger arterial stiffness (ß-stiffness) were measured during the 5-min rest, 30-s countdown (CD) before CPT, 2-min CPT, and 3-min recovery (CPT[1st]) in 15 young adults [age, 28 ± 4 years]. The same protocols were repeated randomly with the second CPT (CPT + CC) or placebo test (PLCB + CC). Results: SBP and DBP increased from baseline in CPT[1st] and CPT + CC under room air (RA) and 40 % N2O, while SBP was lower under N2O than under RA in CPT[1st]. HR in CPT[1st] was lower under N2O than under RA. The change (Δ) in HR was smaller during CPT[1st] than during CPT + CC under N2O, and a similar trend was observed under RA. ΔSBP by CD was lower under N2O than under RA in CPT[1st] but not in CPT + CC. HR increased with CD in CPT + CC but not in CPT[1st] under both RA and N2O. ß-stiffness increased by CD regardless of the pain experience, while it was lower under N2O. Conclusion: Repetitive pain experiences induce a feedforward HR increase. 40 % N2O decreases vascular stiffness, which may attenuate the anticipatory pressor response only when the feedforward HR increase does not exist.
ABSTRACT
In this paper, the problem of spatial signature estimation using a uniform linear array (ULA) with unknown sensor gain and phase errors is considered. As is well known, the directions-of-arrival (DOAs) can only be determined within an unknown rotational angle in this array model. However, the phase ambiguity has no impact on the identification of the spatial signature. Two auto-calibration methods are presented for spatial signature estimation. In our methods, the rotational DOAs and model error parameters are firstly obtained, and the spatial signature is subsequently calculated. The first method extracts two subarrays from the ULA to construct an estimator, and the elements of the array can be used several times in one subarray. The other fully exploits multiple invariances in the interior of the sensor array, and a multidimensional nonlinear problem is formulated. A Gauss-Newton iterative algorithm is applied for solving it. The first method can provide excellent initial inputs for the second one. The effectiveness of the proposed algorithms is demonstrated by several simulation results.
