P. Constantinou

Noise components identification in biomedical signals based on Empirical Mode Decomposition

Hilbert-Huang Transform (HHT) is composed of the Empirical Mode Decomposition (EMD) as the first step of the procedure and Hilbert Spectral analysis (HSA) as the second step. It is a recent tool in the analysis of signals originating from nonlinear processes as well as nonstationary signals. Empirical Mode Decomposition produces a set of Intrinsic Mode Functions and the core idea is based on the assumption that any data consists of different simple intrinsic modes of oscillations. Statistical significance of the Intrinsic Mode Functions and partial signal reconstruction are investigated in this paper. Application of Hilbert-Huang Transform on biomedical signals such as ECG from MIT-BIH database and experimental respiratory signals acquired by means of accelerometers, reveal the adaptive nature of the method.

Interference and compatibility issues between the mobile satellite service and the fixed service in the Ku band

This paper examines the potential interference between the mobile satellite service and the fixed service in the Ku band. At first, the aggregate and the single-entry interference criteria for the terrestrial fixed service stations are calculated. Then, all the parameters that influence the interference magnitude are presented and extensively analyzed. In order to evaluate the impact of each one of them in the interference calculations, different scenarios are taken into consideration and simulations are conducted. The results are thoroughly presented and analyzed.

Neural networks applications for the prediction of propagation path loss in urban environments

This paper presents neural network based models for the prediction of propagation path loss in urban environment. The neural networks are designed separately for line-of-sight (LOS) and non-line-of-sight (NLOS) cases. The performance of the neural models is compared to that of the COST231-Walfisch-Ikegami model, the Walfisch-Bertoni model and the single regression model, based on the absolute mean error, standard deviation and the root mean squared error between predicted and measured values.

Experimental respiratory signal analysis based on Empirical Mode Decomposition

Respiration is a widely used biosignal which is combined with other biosignals in order to extract information about the physiological or pathological conditions that may occur in the development of a treatment. Acquisition of respiration in a clinical environment is usually accomplished by standard hospital equipment and minimum invasive techniques. In this paper a non invasive technique is used for respiration monitoring based on accelerometers. The acquired signal is sampled and transmitted through a wireless sensor network to the gateway point (sink) where it is processed. Empirical Mode Decomposition (EMD) is considered as a method of processing of biosignals such as respiration and the application of the decomposition method in experimental signals acquired by means of a wireless sensor network is evaluated. The processing technique covered in this paper is based on selecting the appropriate signals (IMF) in which respiration is decomposed, by their spectral characteristics that correspond to respiration.

Building penetration measurements for 2.4 GHz broadcasting CDMA system

Measurements have been undertaken as the first phase of an investigation concerned with the design of low power micro cellular point to multipoint broadcasting spread spectrum systems. A prerequisite to the design of these systems is the knowledge of building penetration path loss and indoor radio propagation characteristics. In this study we present the results of the initial phase of the measurement campaign. Penetration loss through concrete buildings, local median variations and cumulative distributions of received signal levels in different areas are discussed.

Measurements for 2.4 GHz spread spectrum system in modern office buildings

Summary form only given. The implementation of wireless communications inside office buildings requires a profound knowledge of signal penetration within buildings. This paper contributes to the modeling of propagation losses and measurement techniques in modern office buildings by presenting measurement results at 2.4 GHz. The measurements were conducted within the National Technical University premises in Athens, Greece. The purpose of the measurement campaign was to study the radio coverage of the three-floor building. The measurement procedure involved field measurements of a spread spectrum system. The measurement system and experimental procedures are described and analysis results are presented. Specifically, path loss is presented as a function of the true and covered distance as well as comparative plots for the corridors and rooms of the three floors of the building. Path loss contour plots are also presented.

Man made noise measurements

Preliminary results on man-made noise in the frequency range of 1 to 3 GHz are presented. The measurements are required for the development of man-made noise models as a function of frequency, time, location, and traffic load. The models will be used for the proposed Universal Mobile Telecommunication System (UMTS). The models will be based on measurements in possible locations where mobile radios and pocket phones will operate. The locations considered for the present study include urban, suburban and rural areas in the vicinity of the city of Athens, Greece.<<ETX>>

Investigating performance of Empirical Mode Decomposition application on electrocardiogam

Empirical Mode Decomposition (EMD) is widely used in biomedical field especially for electrocardiogram (ECG) signal processing. The combination of EMD with Hilbert Transform, the Hilbert Huang Transform (HHT), offers higher frequency resolution and more accurate timing of transient non-stationary signals than conventional integral transform techniques. Embedded computing and signal processing chips with sufficient performance are involved in the application of HHT in data streams. The original HHT algorithm, especially in the case of EMD, is not suitable in such systems so an incremental algorithm is necessary for efficient computation. In this paper an investigation of the EMD performance is presented in terms of computation time that is necessary for smart resource management. A metric is proposed aiming at the a priori calculation of computation time based on ECG time series characteristics.

On the Empirical Mode Decomposition Performance in White Gaussian Noise Biomedical Signals

Empirical Mode Decomposition (EMD) is widely used in biomedical field for electrocardiogram (ECG) processing. Removal of high-frequency noise which is one the main artifacts that corrupt ECG, is carried out by proper selection of Intrinsic Mode Functions (IMF) produced by EMD and partial signal reconstruction. In this paper a study of the influence of White Gaussian Noise in synthetic electrocardiograms of various Signal to Noise ratios (SNR) in terms of total number of Intrinsic Mode Functions is presented. Simulations reveal that a pre-processing stage before the application of EMD optimizes processing time by reducing the total number of IMFs without significant loss of information content.

Feasibility study of coexistence between spread spectrum and analog broadcasting systems

The study considers the viability and limitations of a spread spectrum radio concept. This concept proposed a spectrum overlay of a spread spectrum system on the existing narrowband FM broadcasting system. The overlaid spread spectrum (SS) system is assumed to utilize direct sequence (DS) spreading, using maximal length pseudorandom sequences with long spreading codes. We studied the performance analysis of the SS system due to the overlaying analog FM system, consisting of multiple narrowband FM stations. The received narrowband interference (NBI) on the SS receiver performance was calculated and compared with a set of threshold criteria that derived in previous studies by the authors, in terms of carrier-to-interference ratio (CIR). The probability of error for the SS signal was determined for various types of spreading scenarios, for various signal-to-interference ratios and for different processing gains. The obtained parameters will ascertain the restrictions and the feasibility of the concept.