Abstract—New miniaturized portable ECG measuring devices may require reduced electrode size and distance between the electrodes. Modeling tools can be useful in predicting the behavior of electric field between electrodes. This paper introduces a project where the effect of interelectrode distance (IED) of electrocardiographic (ECG) precordial electrodes was studied with a model of the thorax as a volume conductor and with Body Surface Potential Map (BSPM) data. The objective was to study how the IED affects the signal strength and how well the modeling data corresponds to the clinical data. 2D and 3D Finite Difference Method (FDM) thorax models based on Visible Human Man data were used. On these FDM models, the electrodes’ sensitivity to measure the electric field of the heart was derived. The results were compared to clinical 120 channel BSPM data. It was found out that reducing the IED obviously decreases the signal strength. According to the clinical data, the magnitude of this effect depends on the electrode location. This study indicates that modeling the thorax as a volume conductor can predict the signal strength obtained with given electrode configurations. 3D modeling is more accurate in predicting the signal strength from clinical recordings; however, also simple and fast 2D modeling results show comparable values. Keywords—Electrocardiogram, Finite Difference Method, interelectrode distance, modeling, Body Surface Potential Map Data. I. INTRODUCTION This work is part of a project called Wireless Technology and Psychophysiological computing. The aim of the project is to study wireless sensor technology that can be used for monitoring of behaviors that are related to human physiological and psychophysiological responses. The ultimate goal of the project is to demonstrate the use of lightweight wireless monitoring systems for monitoring the functioning of the human heart (ECG), brain activity (EEG), eye movements (EOG), and facial muscle activity (EMG). The cardiac activity is commonly monitored by the standard 12-lead ECG system or by Body Surface Potential Map (BSPM). In BSPM method, potentials caused by heart’s electric activity are recorded over the whole thorax surface, usually from 120 points. Nowadays, the advancements in wireless and portable technology suggest that the possibilities for smaller measurement devices and configurations taking advantage of miniaturization should be surveyed. It is obvious that decreasing the distance between two electrodes (interelectrode distance, IED) decreases the measuring depth. Accordingly, this causes that signals arising from deeper sources, such as the heart, decrease. Investigating the functionality of electrode systems may be tedious with numerous clinical trials. For this, modeling tools can be useful, because they offer a possibility to study different phenomena even before the actual device is ready. Modeling has been used e.g. for optimizing the electrode positions for defibrillators or for multichannel ECG recording [1-3]. Nevertheless, for one-lead bipolar ECG measurement, the magnitude of the effect of reducing the IED has not been widely studied. In this paper, the effect of reducing the IED on bipolar ECG signal strength was modeled with 2D and 3D thorax models and tested with real BSPM ECG database. The main aim of this project was to evaluate how well 2D and 3D modeling can predict the actual signal strength in clinical data. 2D model was tested since it can provide very fast calculation. II. METHODOLOGY In this project, two methods were used: model of a thorax as a volume conductor and clinical BSPM data. These methods were used for studying the measuring sensitivity and the signal strength in bipolar electrode pairs located in the area of precordial electrodes V1-V6. The location of standard precordial electrodes in 12-lead ECG is illustrated in Fig.1. Fig. 1. Location of the precordial electrodes V1-V6 in the standard 12-lead system ECG recording (modified from [4]). Modeling bipolar ECG signal strength with thorax models and validation of the modeling method M. Puurtinen, J. Hyttinen, J. Viik, P. Kauppinen, J. Malmivuo Ragnar Granit Institute, Tampere University of Technology, Tampere, Finland