DETECTION OF ARTIAL FIBRILLATION DISORDER BY ECG USING DISCRETE WAVELET TRANSFORMS

Atrial fibrillation (A-fib) is the most common cardiac disorder. To efficiently treat or inhibit, an automatic detection based on electrocardiograph (ECG)monitoring is significantly required. ECG is a key function in the analysis of the heart functioning and diagnostic of diseases. Currently, a computer basedsystem is used to analyze the ECG signal. The main aim of this project is to analyze a heart malfunctions named as A-fib, using discrete wavelet transforms(DWT). The ECG signals were decomposed into time-frequency representations using DWT, and the statistical features were calculated to describe theirdistribution. The DWT detailed coefficients are used to obtain various parameters of the ECG signal such as the mean, variance, standard deviation, andentropy of the signal. An analysis had been made with these parameters of various patients with normal heart functioning and A-fib to identify the disorder.Keywords: Atrial fibrillation, Electrocardiogram, Discrete wavelet transforms

Metabolome-Proteome Differentiation Coupled to Microbial Divergence

Tandem high-throughput proteomics and metabolomics were employed to functionally characterize natural microbial biofilm communities. Distinct molecular signatures exist for each analyzed sample. Deconvolution of the high-resolution molecular data demonstrates that identified proteins and detected metabolites exhibit organism-specific correlation patterns. These patterns are reflective of the functional differentiation of two bacterial species that share the same genus and that co-occur in the sampled microbial communities. Our analyses indicate that the two species have similar niche breadths and are not in strong competition with one another

Feasibility of Imaging Photoplethysmography

Contact and spot measurement have limited the application of photoplethysmography (PPG), thus an imaging PPG system comprising a digital CMOS camera and three wavelength light-emitting diodes (LEDs) is developed to detect the blood perfusion in tissue. With the means of the imaging PPG system, the ideally contactless monitoring with larger field of view and the different depth of tissue by applying multi- wavelength illumination can be achieved to understand the blood perfusion change. Corresponding to the individual wavelength LED illumination, the PPG signals can be derived in the both transmission and reflection modes, respectively. The outcome explicitly reveals the imaging PPG is able to detect blood perfusion in a illuminated tissue and indicates the vascular distribution and the blood cell response to individual wavelength LED. The functionality investigation leads to the engineering model for 3-D visualized blood perfusion of tissue and the development of imaging PPG tomography

Principles of visual key construction―with a visual identification key to the Fagaceae of the southeastern United States

We present the first visual, as opposed to illustrated, keys to a group of taxa. The creation of four visual keys to the Fagaceae of the southeastern United States are described, one for each of the following characteristics: leaves, buds, fruits, bark

A survey of current software for network analysis in molecular biology

Software for network motifs and modules is briefly reviewed, along with programs for network comparison. The three major software packages for network analysis, CYTOSCAPE, INGENUITY and PATHWAY STUDIO, and their associated databases, are compared in detail. A comparative test evaluated how these software packages perform the search for key terms and the creation of network from those terms and from experimental expression data

A comparison of several algorithms for the single individual SNP haplotyping reconstruction problem

Motivation: Single nucleotide polymorphisms are the most common form of variation in human DNA, and are involved in many research fields, from molecular biology to medical therapy. The technological opportunity to deal with long DNA sequences using shotgun sequencing has raised the problem of fragment recombination. In this regard, Single Individual Haplotyping (SIH) problem has received considerable attention over the past few years

Classification of Brain Hemorrhage using Textural Analysis

In order to assist in fast diagnosis of brain hemorrhage, computer-aided diagnosis have been developed in recent years. Image processing and analysis is considered to be an important area as technological tool for medical evaluation and diagnosis. With this, we decided to venture in the image processing and analysis of brain hemorrhage. Image processing comprises of different techniques and phases, wherein each techniques intend to contribute to the accuracy of medical diagnosis. With only few studies on image processing for the diagnosis of brain hemorrage, there is a need to improve the algorithm of image processing for accuracy and robustness

Classification of Brain Hemorrhage using Textural Analysis

In order to assist in fast diagnosis of brain hemorrhage, computer-aided diagnosis have been developed in recent years. Image processing and analysis is considered to be an important area as technological tool for medical evaluation and diagnosis. With this, we decided to venture in the image processing and analysis of brain hemorrhage. Image processing comprises of different techniques and phases, wherein each techniques intend to contribute to the accuracy of medical diagnosis. With only few studies on image processing for the diagnosis of brain hemorrage, there is a need to improve the algorithm of image processing for accuracy and robustness

Development of real-time cellular impedance analysis system

The cell impedance analysis technique is a label-free, non-invasive method, which simplifies sample preparation and allows applications requiring unmodified cell retrieval. However, traditional impedance measurement methods suffer from various problems (speed, bandwidth, accuracy) for extracting the cellular impedance information. This thesis proposes an improved system for extracting precise cellular impedance in real-time, with a wide bandwidth and satisfactory accuracy. The system hardware consists of five main parts: a microelectrode array (MEA), a stimulation circuit, a sensing circuit, a multi-function card and a computer. The development of system hardware is explored. Accordingly, a novel bioimpedance measurement method coined digital auto balancing bridge method, which is improved from the traditional analogue auto balancing bridge circuitry, is realized for real-time cellular impedance measurement. Two different digital bridge balancing algorithms are proposed and realized, which are based on least mean squares (LMS) algorithm and fast block LMS (FBLMS) algorithm for single- and multi-frequency measurements respectively. Details on their implementation in FPGA are discussed. The test results prove that the LMS-based algorithm is suitable for accelerating the measurement speed in single-frequency situation, whilst the FBLMS-based algorithm has advantages in stable convergence in multi-frequency applications. A novel algorithm, called the All Phase Fast Fourier Transform (APFFT), is applied for post-processing of bioimpedance measurement results. Compared with the classical FFT algorithm, the APFFT significantly reduces spectral leakage caused by truncation error. Compared to the traditional FFT and Digital Quadrature Demodulation (DQD) methods, the APFFT shows excellent performance for extracting accurate phase and amplitude in the frequency spectrum. Additionally, testing and evaluation of the realized system has been performed. The results show that our system achieved a satisfactory accuracy within a wide bandwidth, a fast measurement speed and a good repeatability. Furthermore, our system is compared with a commercial impedance analyzer (Agilent 4294A) in biological experiments. The results reveal that our system achieved a comparable accuracy to the commercial instrument in the biological experiments. Finally, conclusions are given and the future work is proposed