Haitham M. Al-Angari

Use of Sample Entropy Approach to Study Heart Rate Variability in Obstructive Sleep Apnea Syndrome

Sample entropy, a nonlinear signal processing approach, was used as a measure of signal complexity to evaluate the cyclic behavior of heart rate variability (HRV) in obstructive sleep apnea syndrome (OSAS). In a group of 10 normal and 25 OSA subjects, the sample entropy measure showed that normal subjects have significantly more complex HRV pattern than the OSA subjects (p < 0.005). When compared with spectral analysis in a minute-by-minute classification, sample entropy had an accuracy of 70.3% (69.5% sensitivity, 70.8% specificity) while the spectral analysis had an accuracy of 70.4% (71.3% sensitivity, 69.9% specificity). The combination of the two methods improved the accuracy to 72.9% (72.2% sensitivity, 73.3% specificity). The sample entropy approach does not show major improvement over the existing methods. In fact, its accuracy in detecting sleep apnea is relatively low in the well classified data of the physionet. Its main achievement however, is the simplicity of computation. Sample entropy and other nonlinear methods might be useful tools to detect apnea episodes during sleep.

Atrial fibrillation and waveform characterization

The surface electrocardiogram (ECG) is a convenient, cost effective, and noninvasive tool for the study of atrial fibrillation (AF). It can be used to examine the hypothesized mechanisms of AF as well as to quantify and assess the effect of electrophysiological remodeling and the effectiveness of treatment on different types of AF. Time domain methods can be used to characterize the signal in the surface ECG. The authors described observations that can be obtained directly from the signal, such as the general characteristics of AF in the surface ECG and the ventricular response to AF. A discussion on commonly used methods to characterize atrial activity is also presented. These methods include cancellation techniques, vector analysis, and autocorrelation. Observations show that combining time and frequency domain methods provides a more thorough understanding of the characteristics of the atrial activity in the surface ECG. Whether the study of atrial activity in the surface ECG can be used to distinctively distinguish between different mechanisms of AF is not yet known, but further investigation can improve our understanding of these mechanisms and help with the management of this common arrhythmia

Automated Recognition of Obstructive Sleep Apnea Syndrome Using Support Vector Machine Classifier

Obstructive sleep apnea (OSA) is a common sleep disorder that causes pauses of breathing due to repetitive obstruction of the upper airways of the respiratory system. The effect of this phenomenon can be observed in other physiological signals like the heart rate variability, oxygen saturation, and the respiratory effort signals. In this study, features from these signals were extracted from 50 control and 50 OSA patients from the Sleep Heart Health Study database and implemented for minute and subject classifications. A support vector machine (SVM) classifier was used with linear and second-order polynomial kernels. For the minute classification, the respiratory features had the highest sensitivity while the oxygen saturation gave the highest specificity. The polynomial kernel always had better performance and the highest accuracy of 82.4% (Sen: 69.9%, Spec: 91.4%) was achieved using the combined-feature classifier. For subject classification, the polynomial kernel had a clear improvement in the oxygen saturation accuracy as the highest accuracy of 95% was achieved by both the oxygen saturation (Sen: 100%, Spec: 90.2%) and the combined-feature (Sen: 91.8%, Spec: 98.0%). Further analysis of the SVM with other kernel types might be useful for optimizing the classifier with the appropriate features for an OSA automated detection algorithm.

The optimization of needle electrode number and placement for irreversible electroporation of hepatocellular carcinoma

The optimization of needle electrode number and placement for irreversible electroporation of hepatocellular carcinoma Background. Irreversible electroporation (IRE) is a novel ablation tool that uses brief high-voltage pulses to treat cancer. The efficacy of the therapy depends upon the distribution of the electric field, which in turn depends upon the configuration of electrodes used. Methods. We sought to optimize the electrode configuration in terms of the distance between electrodes, the depth of electrode insertion, and the number of electrodes. We employed a 3D Finite Element Model and systematically varied the distance between the electrodes and the depth of electrode insertion, monitoring the lowest voltage sufficient to ablate the tumor, VIRE. We also measured the amount of normal (non-cancerous) tissue ablated. Measurements were performed for two electrodes, three electrodes, and four electrodes. The optimal electrode configuration was determined to be the one with the lowest VIRE, as that minimized damage to normal tissue. Results. The optimal electrode configuration to ablate a 2.5 cm spheroidal tumor used two electrodes with a distance of 2 cm between the electrodes and a depth of insertion of 1 cm below the halfway point in the spherical tumor, as measured from the bottom of the electrode. This produced a VIRE of 3700 V. We found that it was generally best to have a small distance between the electrodes and for the center of the electrodes to be inserted at a depth equal to or deeper than the center of the tumor. We also found the distance between electrodes was far more important in influencing the outcome measures when compared with the depth of electrode insertion. Conclusions. Overall, the distribution of electric field is highly dependent upon the electrode configuration, but the optimal configuration can be determined using numerical modeling. Our findings can help guide the clinical application of IRE as well as the selection of the best optimization algorithm to use in finding the optimal electrode configuration.

The Improvement of Irreversible Electroporation Therapy Using Saline-Irrigated Electrodes: A Theoretical Study

Irreversible electroporation (IRE) is a novel therapy used to ablate tumors with high-field electric pulses applied in short durations. It is important to reduce the generation of heat in IRE to avoid the harmful effects of thermal damage. The objective of this simulation study was to examine the effects of saline irrigation in the reduction of heat upon electrodes used in IRE treatment of hepatocellular carcinoma. We used a two dimensional Finite Element Model of a tumor in a liver with electrodes placed at the center of the tumor. We simulated a typical electroporation protocol with varying thicknesses and conductivities of the saline layer, and we observed the maximum temperature and the distribution of the electric field and temperature in the tissue. Our results showed that the maximum temperature in the tissue decreases with the use of saline, but the surface area of the tumor that could potentially be thermally damaged may increase with the thickness and conductivity of the saline. With the use of saline, one can achieve upwards of a 17% reduction of the maximum temperature at the electrodes. Also, the distribution of temperature and the electric field becomes more homogenous between the electrodes as the conductivity of the saline layer increases for all thicknesses of saline. We conclude that irrigating electrodes with saline may be an effective measure to enhance the efficacy of irreversible electroporation by reducing the maximum temperature at the electrodes and also improving the extent and distribution of the electric field in the tissue. However, the properties of the saline should be adjusted so as to limit the increase of thermal damage propagated in the tissue.

Electrode Activation Sequencing Employing Conductivity Changes in Irreversible Electroporation Tissue Ablation

Irreversible electroporation (IRE) uses high-voltage pulses applied to tissue, which cause dielectric breakdown of cell membranes resulting in cell death. IRE is a promising technique for ablation of nonresectable tumors because it can be configured to spare critical structures such as blood vessels. A consequence of pulse application is an increase in tissue electrical conductivity due to current pathways being opened in cell membranes. We propose a novel IRE method introducing electrode switching and pulse sequencing in which tissue conductivity is first increased using preparatory pulses in order to form high-conductivity zones, which then helps provide higher electric field intensity within the targeted tissue as subsequent pulses are applied, and hence, enhances the efficiency and selectivity of the IRE treatment. We demonstrate the potential of this method using computational models on simple geometries.