Awad Al-Zaben

Effect of esophagus status and catheter configuration on multiple intraluminal impedance measurements

Multiple intraluminal impedance measurement is used to investigate the esophagus condition. This procedure provides information about the esophagus status, reflux occurrence and clearance mechanism. This paper presents finite-element approximation of the forward problem of the catheter inside the esophagus, relating the real data obtained from multiple intraluminal impedance to the solution obtained from the finite-element approximation. Investigation of the effect of the esophagus status on the impedance, and the correlation between various factors that affect the impedance are presented. The results of this paper provide theoretical bases for relating the esophagus condition to the impedance waveforms.

Statistical performance evaluation of ECG transmission using wireless networks

Abstract This paper presents simulation of the transmission of biomedical signals (using ECG signal as an example) over wireless networks. Investigation of the effect of channel impairments including SNR, pathloss exponent, path delay and network impairments such as packet loss probability; on the diagnosability of the received ECG signal are presented. The ECG signal is transmitted through a wireless network system composed of two communication protocols; an 802.15.4- ZigBee protocol and an 802.11b protocol. The performance of the transmission is evaluated using higher order statistics parameters such as kurtosis and Negative Entropy in addition to the common techniques such as the PRD, RMS and Cross Correlation.

Spectral investigations of intraluminal impedance signals.

In this paper, an investigation of the spectral characteristics of intraluminal impedance signals using local Hilbert–Huang transform is presented. The impedance waveform may contain three main events: reflux event, swallow event and baseline region corresponding to no activity. The three events are analysed using local Hilbert–Huang transform to characterize the frequency contents of each event. In addition to the results of the Hilbert–Huang transform a time domain description of each event is presented.

Telemetry Design of a Vital Sign Recording System

Blood pressure, respiratory rate, body temperature, and pulse rate are vital signs that under certain pathological conditions require continuous monitoring. In this paper we present a novel design of a system that embeds these signals into a single waveform that can be transmitted without the need for time or frequency division multiplexing. The system depends on changing the frequency of a square wave oscillator. One signal with low frequency contents controls the On-time of the oscillator while the Off-time is controlled by another signal. The third and the fourth signals are used to control voltage controlled oscillators. The voltage controlled oscillators outputs are used as fluctuations during the On-time and during the Off-time. The main advantage of this system is the reduction in circuit complexity in both transmitter and receiver with accurate recovery of the transmitted signals. The design of the proposed system is presented in this paper along with all the corresponding simulations.

Extraction of Arterial Blood Pressure Signal from Intraluminal Impedance Signals

Multichannel intraluminal procedure provides information about the esophagus status, reflux occurrence, and clearance mechanism. The study of the impedance signals has been concentrated on the study of reflux patterns and clearance mechanisms. However, there are a number of sources that results in the variations seen in impedance signal. These sources include esophageal characteristic, reflux occurrence, catheter movement, arterial blood pressure and respiration signal. This paper presents the use of the blind signal separation to extract the arterial blood pressure signal from the impedance signals. The extracted signal is further processed to get clean arterial blood pressure signal. The respiration signal can also be extracted in a similar approach

Estimation and compensation of a biomedical sensor's response delay using extended Kalman filter

The use of packaging material in biomedical sensors is a required criterion to achieve certain properties; the most important one is biocompatibility. Response time of biomedical sensors is highly dependent on the sensors specifications in addition to the type of packaging materials. Compensation of the time delay in the sensors response due to the packaging material requires detailed mathematical model of the governing equations in addition to the knowledge of the different packaging layers properties. In this paper, we present the use of extended Kalman filter to estimate the transient response of the sensor without the need to perform such complex mathematical modeling. The idea is to estimate the required response given the measurements model and the packaging effects model to build nonlinear state-measurements equations. The paper also presents the results obtained from simulated and measured selected sensors responses.

Minimum bias metamodels in engineering system design

Experimental designs are techniques used to determine combinations of design variables to generate models of engineering systems. When experiments are conducted using simulators to determine system responses, the resulting approximation to the simulator is called a metamodel or a surrogate model. Accuracy of metamodels is tightly related to experimental designs. Designs that minimise errors caused by metamodel fitting inadequacy - called bias errors - are known as minimum bias designs (MBDs). This paper presents techniques for generating MBDs for use in response surface metamodelling of engineering systems to obtain minimum bias metamodels. The resulting MBDs are compared to the more recent space-filling designs such as the Latin hypercube (LHC) samples. The paper also includes tables of second- to fourth-order MBDs for two- to five-dimensional spaces.

Enhanced segmentation of EOG signals

Extraction of certain events from a signal is a very common problem in the field of medical signal processing. This paper presents a combined method to extract events from electro-oculogram (EOG) signal that are characterized by a band of frequencies. The method uses a combination of mean weighted instantaneous frequency and Pan-Tompkins algorithm. The goal is to improve specifically the identification of the start and end of the detected event. The algorithm is tested and applied on the Electro-oculogram signals and the results are presented.