Comparison of ANN and ANFIS Models for AF Diagnosis Using RR Irregularities

Classification of normal sinus rhythm (NSR), paroxysmal atrial fibrillation (PAF), and persistent atrial fibrillation (AF) is crucial in order to diagnose and effectively plan treatment for patients. Current classification models were primarily developed by electrocardiogram (ECG) signal databases, which may be unsuitable for local patients. Therefore, this research collected ECG signals from 60 local Thai patients (age 52.53 ± 23.92) to create a classification model. The coefficient of variance (CV), the median absolute deviation (MAD), and the root mean square of the successive differences (RMSSD) are ordinary feature variables of RR irregularities used by existing models. The square of average variation (SAV) is a newly proposed feature that extracts from the irregularity of RR intervals. All variables were found to be statistically different using ANOVA tests and Tukey’s method with a p-value less than 0.05. The methods of artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) were also tested and compared to find the best classification model. Finally, SAV showed the best performance using the ANFIS model with trapezoidal membership function, having the highest system accuracy (ACC) at 89.33%, sensitivity (SE), specificity (SP), and positive predictivity (PPR) for NSR at 100.00%, 94.00%, and 89.29%, PAF at 88.00%, 90.57%, and 81.48%, and AF at 80.00%, 96.00%, and 90.91%, respectively

Whole blood viscosity modeling using power law, Casson, and Carreau Yasuda models integrated with image scanning U-tube viscometer technique

This study presented the image scanning U-tube viscometer technique to measure the whole blood viscosity. Two different constitutive models, power law and Casson, were selected to calculate blood viscosity. Results were compared with rotating viscometer. They had a good agreement at higher shear rates. Three constitutive models power law, Casson and Carreau Yasuda models were applied to blood viscosity data and used to simulate transient blood height in the U-tube. Comparison of the U-tube simulation and the actual experiment showed that Carreau Yasuda model is the most accurate model for whole blood viscosity measurement