Evaluation of a combined wavelet and a combined principal component analysis classification system for BCG diagnostic problem

Heart disease is one of the main factor causing death in the developed countries. Over several decades, variety of electronic and computer technology have been developed to assist clinical practices for cardiac performance monitoring and heart disease diagnosis. Among these methods, Ballistocardiography (BCG) has an interesting feature that no electrodes are needed to be attached to the body during the measurement. Thus, it is provides a potential application to asses the patients heart condition in the home. In this paper, a comparison is made for two neural networks based BCG signal classification models. One system uses a principal component analysis (PCA) method, and the other a discrete wavelet transform, to reduce the input dimensionality. It is indicated that the combined wavelet transform and neural network has a more reliable performance than the combined PCA and neural network system. Moreover, the wavelet transform requires no prior knowledge of the statistical distribution of data samples and the computation complexity and training time are reduced.

Surface Perception from Local Analysis of Texture and Contour

The visual analysis of surface shape from texture and surface contour is treated within a computational framework. The aim of this study is to determine valid constraints that are sufficient to allow surface orientation and distance (up to a multiplicative constant) to be computed from the image of surface texture and of surface contours.

Wavelet phase coherence analysis: Application to a quiet-sun magnetic element

A new application of wavelet analysis is presented that utilizes the inherent phase information residing within the complex Morlet transform. The technique is applied to a weak solar magnetic network region, and the temporal variation of phase difference between TRACE 1700 Angstrom and SOHO/SUMER C II 1037 Angstrom intensities is shown. We present, for the first time in an astrophysical setting, the application of wavelet phase coherence, including a comparison between two methods of testing real wavelet phase coherence against that of noise. The example highlights the advantage of wavelet analysis over more classical techniques, such as Fourier analysis, and the effectiveness of the former to identify wave packets of similar frequencies but with differing phase relations is emphasized. Using cotemporal, ground-based Advanced Stokes Polarimeter measurements, changes in the observed phase differences are shown to result from alterations in the magnetic topology.

Texture profile analysis of bioadhesive polymeric semisolids: Mechanical characterization and investigation of interactions between formulation components

This study reports the use of texture profile analysis (TPA) to mechanically characterize polymeric, pharmaceutical semisolids containing at least one bioadhesive polymer and to determine interactions between formulation components. The hardness, adhesiveness, force per unit time required for compression (compressibility), and elasticity of polymeric, pharmaceutical semisolids containing polycarbophil (1 or 5% w/w), polyvinylpyrrolidone (3 or 5% w/w), and hydroxyethylcellulose (3, 5, or 10% w/w) in phosphate buffer (pH 6.8) were determined using a texture analyzer in the TPA mode (compression depth 15 mm, compression rate 8 mm s(-1) 15 s delay period). Increasing concentrations of polycarbophil, poly vinylpyrrolidone, and hydroxyethylcellulose significantly increased product hardness, adhesiveness, and compressibility but decreased product elasticity. Statistically, interactions between polymeric formulation components were observed within the experimental design and were probably due to relative differences in the physical states of polyvinylpyrrolidone and polycarbophil in the formulations, i.e., dispersed/dissolved and unswollen/swollen, respectively. Increased product hardness and compressibility were possibly due to the effects of hydroxyethylcellulose, polyvinylpyrrolidone, and polycarbophil on the viscosity of the formulations. Increased adhesiveness was related to the concentration and, more importantly, to the physical state of polycarbophil. Decreased product elasticity was due to the increased semisolid nature of the product. TPA is a rapid, straightforward analytical technique that may be applied to the mechanical characterization of polymeric, pharmaceutical semisolids. It provides a convenient means to rapidly identify physicochemical interactions between formulation components. (C) 1996 John Wiley & Sons, Inc.

Wavelet analysis of bender element signals

Accurate determination of shear wave arrival time using bender elements may be severely affected by a combination of near-field effects and reflected waves. These may mask the first arrival of the shear wave, making its detection difficult in the time domain. This paper describes an approach for measuring the shear wave arrival time through analysis of the output signal in the time-scale domain using a multi-scale wavelet transform. The local maxima lines of the wavelet transform modulus are observed at different scales, and all singularities are mathematically characterised, allowing subsequent detection of the singularity relating to the first arrival. Examples of the use of this approach on typical synthetic and experimental bender element signals are also supplied, and these results are compared with those from other time and frequency domain approaches. The wavelet approach is not affected by near-field effects, but instead is characterised by a relatively consistent singularity related to the shear wave arrival time, across a range of frequencies and noise levels.