Performance Evaluation of Time-Frequency Distributions for ECG Signal Analysis.

The non-stationary and multi-frequency nature of biomedical signal activities makes the use of time-frequency distributions (TFDs) for analysis inevitable. Time-frequency analysis provides simultaneous interpretations in both time and frequency domain enabling comprehensive explanation, presentation and interpretation of electrocardiogram (ECG) signals. The diversity of TFDs and specific properties for each type show the need to determine the best TFD for ECG analysis. In this study, a performance evaluation of five TFDs in term of ECG abnormality detection is presented. The detection criteria based on extracted features from most important ECG signal components (QRS) to detect normal and abnormal cases. This is achieved by estimating its energy concentration magnitude using the TFDs. The TFDs analyse ECG signals in one-minute interval instead of conventional time domain approach that analyses based on beat or frame containing several beats. The MIT-BIH normal sinus rhythm ECG database total records of 18 long-term ECG sampled at 128 Hz have been analysed. The tested TFDs include Dual-Tree Wavelet Transform, Spectrogram, Pseudo Wigner-Ville, Choi-Williams, and Born-Jordan. Each record is divided into one-minute slots, which is not considered previously, and analysed. The sample periods (slots) are randomly selected ten minutes interval for each record. This result with 99.44% detection accuracy for 15,735 ECG beats shows that Choi-Williams distribution is most reliable to be used for heart problem detection especially in automated systems that provide continuous monitoring for long time duration.

Analysis of Gln223Agr polymorphism of Leptin Receptor Gene in type II diabetic mellitus subjects among Malaysians.

Leptin is known as the adipose peptide hormone. It plays an important role in the regulation of body fat and inhibits food intake by its action. Moreover, it is believed that leptin level deductions might be the cause of obesity and may play an important role in the development of Type 2 Diabetes Mellitus (T2DM), as well as in cardiovascular diseases (CVD). The Leptin Receptor (LEPR) gene and its polymorphisms have not been extensively studied in relation to the T2DM and its complications in various populations. In this study, we have determined the association of Gln223Agr loci of LEPR gene in three ethnic groups of Malaysia, namely: Malays, Chinese and Indians. A total of 284 T2DM subjects and 281 healthy individuals were recruited based on International Diabetes Federation (IDF) criteria. Genomic DNA was extracted from the buccal specimens of the subjects. The commercial polymerase chain reaction (PCR) method was carried out by proper restriction enzyme MSP I to both amplify and digest the Gln223Agr polymorphism. The p-value among the three studied races was 0.057, 0.011 and 0.095, respectively. The values such as age, WHR, FPG, HbA1C, LDL, HDL, Chol and Family History were significantly different among the subjects with Gln223Agr polymorphism of LEPR (p < 0.05).

Review of numerical methods for simulation of mechanical heart valves and the potential for blood clotting.

Even though the mechanical heart valve (MHV) has been used routinely in clinical practice for over 60 years, the occurrence of serious complications such as blood clotting remains to be elucidated. This paper reviews the progress that has been made over the years in terms of numerical simulation method and the contribution of abnormal flow toward blood clotting from MHVs in the aortic position. It is believed that this review would likely be of interest to some readers in various disciplines, such as engineers, scientists, mathematicians and surgeons, to understand the phenomenon of blood clotting in MHVs through computational fluid dynamics.

Association of Cholesteryl Ester Transfer Protein and Endothelial Nitric Oxide Synthase Gene Polymorphisms With Coronary Artery Disease in the Multi-Ethnic Malaysian Population.

Genetic variants of cholesteryl ester transfer protein (CETP) and endothelial nitric oxide synthase (eNOS) influence high-density lipoprotein cholesterol (HDL-C) metabolism and nitric oxide (NO) synthesis, respectively, and might increase the risk of coronary artery disease (CAD). This study is to investigate the relationship between genetic polymorphisms and the risk of CAD and to evaluate their potential interactions. A total of 237 patients with CAD and 101 controls were genotyped. The association of the polymorphism with the risk of CAD varied among the ethnic groups. Moreover, the concomitant presence of both CETP B1 and eNOS 4a alleles significantly increased the risk of CAD in the Malay group (OR = 33.8, P < .001) and the Indian group (OR = 10.9, P = .031) but not in the Chinese group. This study has identified a novel ethnic-specific gene-gene interaction and suggested that the combination of CETP B1 allele and eNOS 4a allele significantly increases the risk of CAD in Malays and Indians.