Classical regression equations of spirometric parameters are not applicable for diagnosing spirometric abnormalities in adipotic adults

The prevalence of overweighing and obese adults (defined as "adipotic" adults),has markedly increased over the world. A remarkable increase in the adipotic population urgently needs developing the regression equations for predicting spirometric parameters (SPs), which are specifically applicable to adipotic adults.Unfortunately, however, the reliable equations suitable for adipotic adults have not been reported to date. Recently, Yamaguchi et al have proposed the quantitative method to estimate the effects of adiposity on deciding the SPs incorporating with age-specific contributions of various explanatory,independent variables such as age (A), standing height (H), body weight (BW),and fat fraction of body mass(F). Extending the method proposed by Yamaguchi et al, we attempted to elaborate the novel regression equations applicable for diagnosing the spirometric abnormality in adipotic adults. For accomplishing this purpose, never-smoking, adipotic adults with body mass index (BMI) over 25 kg/m^2 and no respiratory illness were recruited from the general population in Japan (n = 3696, including men: 1890 and women: 1806). Introducing the four explanatory variables of A, H, BW, and F, gender-specific and age-dependent regression equations that allowed for prescribing the SPs in adipotic adults were constructed. Comparing the results obtained for non-adipotic adults (i.e., those with normal BMI), the negative or positive impact of height on SPs was preserved in adipotic adults, as well. However, the negative impact of age on SPs was blunted in adipotic men and the positive effect of BW on SPs was impeded in adipotic men and women. The fat fraction of body mass-elicited negative impact on SPs vanished in adipotic women. These results indicate that the regression equations of SPs for adipotic adults differ significantly from those for nonadipotic adults, leading to the conclusion that the regression equations for nonadipotic adults should not be used while judging the spirometric abnormalities in adipotic adults.

Demodulation method combining virtual reference interferometry and minimum mean square error for fiber-optic Fabry–Perot sensors

We propose a cavity length demodulation method that combines virtual reference interferometry（VRI） and minimum mean square error（MMSE） algorithm for fiber-optic Fabry–Perot（F-P） sensors. In contrast to the conventional demodulating method that uses fast Fourier transform（FFT） for cavity length estimation,our method employs the VRI technique to obtain a raw cavity length, which is further refined by the MMSE algorithm. As an experimental demonstration, a fiber-optic F-P sensor based on a sapphire wafer is fabricated for temperature sensing. The VRI-MMSE method is employed to interrogate cavity lengths of the sensor under different temperatures ranging from 28°C to 1000°C. It eliminates the ＂mode jumping＂ problem in the FFT-MMSE method and obtains a precision of 4.8 nm, corresponding to a temperature resolution of 2.0°C over a range of 1000°C. The experimental results reveal that the proposed method provides a promising, high precision alternative for demodulating fiber-optic F-P sensors.