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Dynamic ECG features for atrial fibrillation recognition

Abdul-Kadir NA, Mat Safri N, Othman MA

Comput Methods Programs Biomed, 2016 Nov;136:143-50.
PMID: 27686711 DOI: 10.1016/j.cmpb.2016.08.021

BACKGROUND: Atrial fibrillation (AF) can cause the formation of blood clots in the heart. The clots may move to the brain and cause a stroke. Therefore, this study analyzed the ECG features of AF and normal sinus rhythm signals for AF recognition which were extracted by using a second-order dynamic system (SODS) concept.
OBJECTIVE: To find the appropriate windowing length for feature extraction based on SODS and to determine a machine learning method that could provide higher accuracy in recognizing AF.
METHOD: ECG features were extracted based on a dynamic system (DS) that uses a second-order differential equation to describe the short-term behavior of ECG signals according to the natural frequency (ω), damping coefficient, (ξ), and forcing input (u). The extracted features were windowed into 2, 3, 4, 6, 8, and 10 second episodes to find the appropriate windowing size for AF signal processing. ANOVA and t-tests were used to determine the significant features. In addition, pattern recognition machine learning methods (an artificial neural network (ANN) and a support vector machine (SVM)) with k-fold cross validation (k-CV) were used to develop the ECG recognition system.
RESULTS: Significant differences (p
Atrial fibrillation classification and association between the natural frequency and the autonomic nervous system

Abdul-Kadir NA, Mat Safri N, Othman MA

Int J Cardiol, 2016 Nov 01;222:504-8.
PMID: 27505342 DOI: 10.1016/j.ijcard.2016.07.196

BACKGROUND: The feasibility study of the natural frequency (ω) obtained from a second-order dynamic system applied to an ECG signal was discovered recently. The heart rate for different ECG signals generates different ω values. The heart rate variability (HRV) and autonomic nervous system (ANS) have an association to represent cardiovascular variations for each individual. This study further analyzed the ω for different ECG signals with HRV for atrial fibrillation classification.
METHODS: This study used the MIT-BIH Normal Sinus Rhythm (nsrdb) and MIT-BIH Atrial Fibrillation (afdb) databases for healthy human (NSR) and atrial fibrillation patient (N and AF) ECG signals, respectively. The extraction of features was based on the dynamic system concept to determine the ω of the ECG signals. There were 35,031 samples used for classification.
RESULTS: There were significant differences between the N & NSR, N & AF, and NSR & AF groups as determined by the statistical t-test (p<0.0001). There was a linear separation at 0.4s(-1) for ω of both databases upon using the thresholding method. The feature ω for afdb and nsrdb falls within the high frequency (HF) and above the HF band, respectively. The feature classification between the nsrdb and afdb ECG signals was 96.53% accurate.
CONCLUSIONS: This study found that features of the ω of atrial fibrillation patients and healthy humans were associated with the frequency analysis of the ANS during parasympathetic activity. The feature ω is significant for different databases, and the classification between afdb and nsrdb was determined.
Fulltext Protective Effects of Tamarillo (Cyphomandra betacea) Extract against High Fat Diet Induced Obesity in Sprague-Dawley Rats

Abdul Kadir NA, Rahmat A, Jaafar HZ

J Obes, 2015;2015:846041.
PMID: 26171246 DOI: 10.1155/2015/846041

This study aims to investigate the protective effect of Cyphomandra betacea in adult male Sprague-Dawley rats fed with high fat diet. Rats were fed on either normal chow or high fat diet for 10 weeks for obesity induction phase and subsequently received C. betacea extract at low dose (150 mg kg(-1)), medium dose (200 mg kg(-1)), or high dose (300 mg kg(-1)) or placebo via oral gavages for another 7 weeks for treatment phase. Treatment of obese rats with C. betacea extracts led to a significant decrease in total cholesterol and significant increase in HDL-C (p < 0.05). Also there was a trend of positive reduction in blood glucose, triglyceride, and LDL-C with positive reduction of body weight detected in medium and high dosage of C. betacea extract. Interestingly, C. betacea treated rats showed positive improvement of superoxide dismutase (SOD) activity and glutathione peroxidase (GPx) activity along with a significant increase of total antioxidant status (TAS) (p < 0.05). Further, rats treated with C. betacea show significantly lower in TNF-α and IL-6 activities (p < 0.05). This study demonstrates the potential use of Cyphomandra betacea extract for weight maintenance and complimentary therapy to suppress some obesity complication signs.
Fulltext Antioxidant activity, nutritional and physicochemical characteristics, and toxicity of minimally refined brown sugar and other sugars

Azlan A, Khoo HE, Sajak AAB, Aizan Abdul Kadir NA, Yusof BNM, Mahmood Z, et al.

Food Sci Nutr, 2020 Sep;8(9):5048-5062.
PMID: 32994965 DOI: 10.1002/fsn3.1803

Minimally refined brown sugar (MRBS) is a brown sugar derived from sugarcane that has a low glycemic index. This study aimed to determine and compare the antioxidant contents and nutritional and physicochemical properties of MRBS, refined sugar (RS), and brown sugar (BS). In addition, the toxicity of these sugars was evaluated via in vitro cytotoxicity method and by using a zebrafish model. Results showed that MRBS was better than the two other sugars because it has a lower moisture content and higher ash content. The contents of potassium and manganese of MRBS were higher than those of the two other sugars. Surprisingly, MRBS also contained selenium, which was not detected in RS and BS. The major phenolics in MRBS are 4-hydroxybenzoic acid, chlorogenic acid, protocatechuic acid, trans-Ferulic acid, and apigenin. All sugar solutions and their antioxidant-containing extracts were not cytotoxic to 3T3-L1 adipocytes.