A Review on Magnetic Induction Spectroscopy Potential for Fetal Acidosis Examination.

Fetal acidosis is one of the main concerns during labor. Currently, fetal blood sampling (FBS) has become the most accurate measurement of acidosis detection. However, it is invasive and does not provide a real time measurement due to laboratory procedures. Delays in diagnosis of acidosis have caused serious injury to the fetus, especially for the brain and the heart. This paper reviews the new technique in diagnosis of acidosis non-invasively. Magnetic Induction Spectroscopy (MIS) has been proposed to be a new device for acidosis detection in recent years. This paper explains the basic principle of MIS and outlines the design specifications and design considerations for a MIS pH probe. It is expected that readers will gain a basic understanding of the development of a MIS pH probe from this review.

Advancements in transmitters and sensors for biological tissue imaging in magnetic induction tomography.

Magnetic Induction Tomography (MIT), which is also known as Electromagnetic Tomography (EMT) or Mutual Inductance Tomography, is among the imaging modalities of interest to many researchers around the world. This noninvasive modality applies an electromagnetic field and is sensitive to all three passive electromagnetic properties of a material that are conductivity, permittivity and permeability. MIT is categorized under the passive imaging family with an electrodeless technique through the use of excitation coils to induce an electromagnetic field in the material, which is then measured at the receiving side by sensors. The aim of this review is to discuss the challenges of the MIT technique and summarize the recent advancements in the transmitters and sensors, with a focus on applications in biological tissue imaging. It is hoped that this review will provide some valuable information on the MIT for those who have interest in this modality. The need of this knowledge may speed up the process of adopted of MIT as a medical imaging technology.

Neural network and principal component regression in non-destructive soluble solids content assessment: a comparison.

Visible and near infrared spectroscopy is a non-destructive, green, and rapid technology that can be utilized to estimate the components of interest without conditioning it, as compared with classical analytical methods. The objective of this paper is to compare the performance of artificial neural network (ANN) (a nonlinear model) and principal component regression (PCR) (a linear model) based on visible and shortwave near infrared (VIS-SWNIR) (400-1000 nm) spectra in the non-destructive soluble solids content measurement of an apple. First, we used multiplicative scattering correction to pre-process the spectral data. Second, PCR was applied to estimate the optimal number of input variables. Third, the input variables with an optimal amount were used as the inputs of both multiple linear regression and ANN models. The initial weights and the number of hidden neurons were adjusted to optimize the performance of ANN. Findings suggest that the predictive performance of ANN with two hidden neurons outperforms that of PCR.

Infrared tomography: data distribution system and software development for real-time velocity measurement.

The data distribution system of this project is divided into two types, which are a Two-PC Image Reconstruction System and a Two-PC Velocity Measurement System. Each data distribution system is investigated to see whether the results' refreshing rate of the corresponding measurement can be greater than the rate obtained by using a single computer in the same measurement system for each application. Each system has its own flow control protocol for controlling how data is distributed within the system in order to speed up the data processing time. This can be done if two PCs work in parallel. The challenge of this project is to define the data flow process and critical timing during data packaging, transferring and extracting in between PCs. If a single computer is used as a data processing unit, a longer time is needed to produce a measurement result. This insufficient real-time result will cause problems in a feedback control process when applying the system in industrial plants. To increase the refreshing rate of the measurement result, an investigation on a data distribution system is performed to replace the existing data processing unit.

Lensed optical fiber sensors for on-line measurement of flow.

This paper describes a system using lensed optical fiber sensors that are arranged in the form of two orthogonal projections. The sensors are placed around a process vessel for upstream and downstream measurements. The purpose of the system is for on-line monitoring of particles and droplets being conveyed by a fluid. The lenses were constructed using a custom heating fixture. The fixture enables the lenses to be constructed with similar radii resulting in identical characteristics with minimum differences in transmitted intensity and emission angle. By collimating radiation from two halogen bulbs, radiation can be obtained by the sensors with radiation intensity related to the nature of the media. Each sensor interrogates a finite section of the measurement section. Each sensor provides a view. Parallel sensors provide a projection. Signal processing is carried out on the measured data in the time and frequency domains to investigate the latent information present in the flow signals.