ABSTRACT
ABSTRACT For computerized analysis of respiratory sounds to be effective, the acquired signal must be free from all the interfering elements. Different forms of noise which can degrade the quality of lung sounds are recording artifacts, power line/Radio Frequency (RF) interferences, ambient acoustic interferences, heart sound interference etc. Such interferences adversely affect the diagnostic interpretations. Powerful denoising techniques are necessary to resolve this issue. A denoising scheme for lung sounds, based on Savitzky-Golay (S-G) filter is proposed in this paper. The order and frame length of the SG filter is determined objectively using the Signal to Noise Ratio (SNR) and computational time as objective function. Maximum SNR is observed when the frame length is nearest to the value just higher than the polynomial order. This observation holds good for different levels of simulated addictive Gaussian noise. The polynomial order of 8 and frame size of 9 are found to be promising with SNR of 10.401db at computation time of 2.1ms.
ABSTRACT
OBJECTIVE:To establish the method for rapid judgement of blending endpoint of Jingqi shuangshen capsules and content determination of astragaloside Ⅳ. METHODS:AOTF-NIR combined with principal component analysis and Moving Block Standard Deviation method was used to identify the blending endpoint. First derivative combined with savitzky-golay filter method were used to spectrum pretreatment. The partial least square method was used to establish quantitative analysis model of the content of astragaloside Ⅳin mixed endpoint sample. The content of astragaloside Ⅳ in mixed endpoint sample was determined by HPLC-ELSD to validate the model. RESULTS:Methodology validation of content determination of astragaloside Ⅳ in mixed material sample and mixed endpoint sample was in line with the requirements. NIR monitoring results showed that the product reached the blending endpoint after 30 min. The results of NIR monitoring were generally consistent with the results of HPLC-ELSD. The principal component dimension of the quantitative model was 9;determination coefficients was 0.954 9;Root Mean Square of Calibration of the model was 0.039 2;Root Mean Square Error of Prediction of the model was 0.042 6. Predicted average value of astragaloside Ⅳ by NIR was 11.74 mg/g,and measured average value of astragaloside Ⅳ by HPLC-ELSD was 11.38 mg/g;average deviation was 3.16%. CONCLUSIONS:AOTF-NIR can rapidly judge the blending endpoint sample of Jingqi shuangshen capsules,rapidly determine the content of astragalosideⅣin mixed endpoint material,improve the quality control level of blending process and shorten blending cycle.