CARDIOSCOPE SIMULATOR SYSTEM Zenon Chaczko and Hany Shehata ICT Group, Faculty of Engineering, University of Technology, Sydney, Australia zenon.chaczko@uts.edu.au , Hany.E.Shehata@eng.uts.edu.au ABSTRACT There is a need for effective, reliable and economic diagnostic technique to detect heart problems at an early stage. This paper presents an innovative approach to the ECG diagnostic modeling that considers a representation of the Inverse problem in multi- dimensional space. Assumptions are made regarding the shape and values for the electrical sources inside the human heart in order to estimate the body surface electrical potentials. An analytical set of expressions used in the proposed diagnostic model combined with the effect of associated source parameters is discussed, analysed and verified. The paper introduces an innovative Inverse problem method for determining the inner heart electrical activity parameters. Results can be then visualized given availability of a stream of body surface potential data. WSN technology is to be applied for collecting and processing diagnostic data. Keywords: ECG diagnostic model, cardioscope, simulation model 1. INTRODUCTION The ECG is considered to be one of the oldest (Einthoven 1908), and most reliable techniques for detection of heart abnormalities. Inevitably, it is one of very few techniques that can also be used for construction of predictive diagnostic models of the electrical activity of the heart. The reliability of ECG method depends on two important factors: 1. Quality and accuracy of statistical data that allows accumulation and correction of ECG shapes with types of diseases causing it. The ECG involves recording electrical signals measured from human body and reflecting electrical activities of the heart. Also, the method can be used to calculate characteristic parameters of the heart from captured electrical signals at the human body. 2. Cardiologists’ experience and diagnostic skills in analysing heart problems using ECG technique. The training of cardiologist takes time. There are recorded cases (and undoubtedly, there will be such cases in the future) which impose critical situations, where a doctor’s indecision is intolerable as only a decision taken fast can save patient’s life. For the reasons stated above, the research studies of the heart functions should extensively stress the need for modeling, analysis and diagnosis of the heart problems taking not only predominantly medical but also an engineering point of view. Two complementary techniques that use mathematical apparatus in construction of electric models contribute to formulation of ECG solution. The first technique allows building an abstract model representing the system and then examines the effect of the assumed parameters. This technique of computing ECG is also known as the forward problem. The second technique, which is based on the forward problem, is termed the inverse problem. It stars from available body surface potential data and ends up with recognizable electrical activities that can help in diagnosing heart problems. In the literature, both techniques are equally well covered. In our study, the emphasis is on the inverse problem. Since both problems are complementary, it is necessary to include some analysis of the forward problem. The introductory part will provide a brief description of the electric activity of the heart including the internal sequences of excitation and an overview of the system used to measure the ECG. The analytical stage is divided into three sections: (1) a calculation model for measuring body surface potentials, (2) collection of readings from the chest leads connectors (as originally postulated by Einthoven) and (3) the image reconstruction of the heart dipole vector that can be used to study the nature of ECG waves for diagnostic purposes. This paper presents an innovative and simplified approach to the ECG diagnostic modeling that considers the representation of the Inverse problem in multi- dimensional space (in this study 2D only). Firstly, an analytical set of expressions for the proposed simplified model is elaborated on, and then the effect of source parameters is verified and analysed. Finally, a new approach to solve the inverse problem itself is presented. The process of Fourier series analysis helps to extract information about the source parameters embedded in the surface potential data. These parameters help to determine the electrical source width angle in a real time. The main aim is to provide an improved model for the human body for ECG purpose. The model is used to estimate the body surface electrical potential. Assuming a certain shape and value for the electrical source inside the human heart we calculate the body surface potential. The research also aims to introduce a method for 15