Modelling the input-output behaviour of piezoelectric structural health monitoring systems for composite plates

This paper investigates the input-output characteristics of structural health monitoring systems for composite plates based on permanently attached piezoelectric transmitter and sensor elements. Using dynamic piezoelectricity theory and a multiple integral transform method to describe the propagating and scattered flexural waves an electro-mechanical model for simulating the voltage input-output transfer function for circular piezoelectric transmitters and sensors adhesively attached to an orthotropic composite plate is developed. The method enables the characterization of all three physical processes, i.e. wave generation, wave propagation and wave reception. The influence of transducer, plate and attached electrical circuit characteristics on the voltage output behaviour of the system is examined through numerical calculations, both in frequency and the time domain. The results show that the input-output behaviour of the system is not properly predicted by the transducers' properties alone. Coupling effects between the transducers and the tested structure have to be taken into account, and adding backing materials to the piezoelectric elements can significantly improve the sensitivity of the system. It is shown that in order to achieve maximum sensitivity, particular piezoelectric transmitters and sensors need to be designed according to the structure to be monitored and the specific frequency regime of interest.

Using patients' and rheumatologists' opinions to specify a short form of the WOMAC function subscale

Background: The WOMAC ( Western Ontario and McMaster Universities) function subscale is widely used in clinical trials of hip and knee osteoarthritis. Reducing the number of items of the subscale would enhance efficiency and compliance, particularly for use in clinical practice applications. Objective: To develop a short form of the WOMAC function subscale based on patients' and experts' opinions ( WOMAC function short form). Methods: WOMAC function subscale data ( Likert version) were obtained from 1218 outpatients with painful hip or knee osteoarthritis. These patients and their rheumatologists selected the five items that they considered most in need of improvement. The rheumatologists were asked to select the five items for which patients in general are the most impaired. Items that were least important to patients and experts, those with a high proportion of missing data, and those with a response distribution showing a floor or ceiling response were excluded, along with one of a pair of items with a correlation coefficient >0.75. Results: The WOMAC function short form included items 1, 2, 3, 6, 7, 8, 9, and 15 of the long form. The short form did not differ substantially from the long form in responsiveness ( standardised response mean of 0.84 v 0.80). Conclusions: A short form of the WOMAC function subscale was developed according to the views of patients and rheumatologists, based on the responses of 1218 patients and 399 rheumatologists. The clinical relevance and applicability of this WOMAC function subscale short form require further evaluation.

Determinants of functional capacity in patients with chronic heart failure: Role of filling pressure and systolic and diastolic function

Background Previous work suggesting a better correlation of diastolic than systolic function with exercise capacity in heart failure may reflect the -relative insensitivity and load-dependence of ejection fraction (EF). We sought the correlation of new and more sensitive methods of quantifying systolic and diastolic function and filling pressure with functional capacity. Methods We studied 155 consecutive exercise tests on 95 patients with congestive heart failure (81 male, aged 62 +/- 10 years), who underwent resting 2-climensional echocardiography and tissue Doppler imaging before and after measurement of maximum oxygen uptake (peak VO2)Results The resting EF was 3 1 % 10% and a peak VO(2)was 13 +/- 5 mL/kg/min; the majority of these patients (80%) had an ischemic cardiornyopathy. Resting EF (r 0.14, P =.09) correlated poorly with peak VO2 and mean systolic (r = 0.23, P =.004) and diastolic tissue velocities (r 0.18, P =.02). Peak EF was weakly correlated with the mean systolic (r = 0.18, P =.02) and diastolic velocities (r = 0.16, P <.04). The mean sum of systolic and diastolic velocities in both annuli (r = 0.30, P <.001) and E/Ea ratio (r 0.31, P <.001) were better correlated with peak VO2 Prediction of peak VO2 was similar with models based on models of filling pressure (R = 0.61), systolic factors (R = 0.63), and diastolic factors (R 0.59), although a composite model of filling pressure, systolic and diastolic function was a superior predictor of peak VO2 (R 0.69; all P<.001). Conclusions The reported association of diastolic rather than systolic function with functional capacity may have reflected the limitations of EF. Functional capacity appears related not only to diastolic function, but also to systolic function and filling pressure, and is most closely associated with a combination of these factors.