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Determination of the optode array representation using optical properties at systole and diastole

Jumadi N A, Beng G K, Mohd-Ali M. A., Zahedi E

Optica Applicata

2013

Vol. 43, nr 4

747--759

The necessity to develop an optode array in order to probe the fetus oxygenation noninvasively regardless of the fetus position has been highlighted in previous literature. In this paper, a series of optical simulations are carried out to determine the best representation of optode array by using optical properties at systolic and diastolic states. The selection is based on the highest flux values accumulated at respective detectors. To accomplish the objective, a homogenous three-layer semi-infinite tissue model is implemented to represent the pregnant woman model. The geometry of the model as well as Monte Carlo simulation are carried out using commercial software, whereas the optical properties related to systolic and diastolic states are defined for all wavelengths. A statistical noise analysis is also introduced in order to find a sufficient number of rays to be launched into the optical tissue system.

Machine learning in lung sound analysis: a systematic review

Palaniappan R., Sundaraj K., Ahamed N. U.

Biocybernetics and Biomedical Engineering

2013

Vol. 33, no. 3

129--135

Machine learning has proven to be an effective technique in recent years and machine learning algorithms have been successfully used in a large number of applications. The development of computerized lung sound analysis has attracted many researchers in recent years, which has led to the implementation of machine learning algorithms for the diagnosis of lung sound. This paper highlights the importance of machine learning in computer-based lung sound analysis. Articles on computer-based lung sound analysis using machine learning techniques were identified through searches of electronic resources, such as the IEEE, Springer, Elsevier, PubMed and ACM digital library databases. A brief description of the types of lung sounds and their characteristics is provided. In this review, we examined specific lung sounds/disorders, the number of subjects, the signal processing and classification methods and the outcome of the analyses of lung sounds using machine learning methods that have been performed by previous researchers. A brief description on the previous works is thus included. In conclusion, the review provides recommendations for further improvements.

Statistical methods in diagnostic of rotor systems

Vekteris V. J., Cereska A.

Mechanics and Mechanical Engineering

2002

Vol. 6, nr 2

65-75

The paper deals with the applying of statistical methods for diagnostic measurements of rotor systems. The methodology of statistical investigation and the procedure of the transducing of the random signal are described. Results of measurements are analyzed and discussed. Corresponding graphs are given.