A new algorithm based Emperical Mode Decomposition (EMD) for the enhancement of bipolar impedance cardiography 3rd International Conference on Embedded Systems in Telecommunications and Instrumentation (ICESTI’16): October 24-26, 2016, Annaba, Algeria S. BENOUAR, A. HAFID, K. MEDDAH, M. KEDIR -TALHA, M. ATTARI USTHB , Electronics and Informatics faculty, Laboratory of Instrumentation (LINS), P. Box 32,Bab-Ezzouar Algiers, Algeria Sara_benouar@hotmail.fr An evaluation of signal recorded from impedance cardiography (ICG) using the basic bipolar configuration with AD5933 analyzer was performed. The algorithm was built on three main parts. The first part, is a pre-filtering stage, based on the Empirical Mode Decomposition (EMD) technics. The second part, is the selection of the significant Intrinsic Mode Functions (IMFs), to reconstruct the meaningful part of the recorded signal. The third part of the algorithm was inspired from Tompkins algorithm with some modified stapes to adapt the algorithm to the studied signal. Finally, the steps of the proposed algorithm were implemented on Matlab, to evaluate the quality of the obtained signals. The calculated Heart rates were compared to those obtained with commercial devices and the results shows a high average similarity. ABSTRACT Intrinsic Mode Functions (IMF) Selection First, for each IMF, we identify the energetic band. we proceed by a fast Fourier transform FFT and Computing a measurement of the energy at various frequencies, using the complex conjugate and the power spectral density (PSD). Extract the prominent frequency peaks. Heart rate (HR) detection algorithm In this work, we are mainly interested in one of the most used medical emergency equipment and personnel health care monitoring, which is impedance cardiography. The Impedance Cardiography (ICG) have been chosen such as an alternative method for most commonly used ones, as the thermodilution catheter, which is invasive, expensive and may be dangerous. further, echocardiography and electrocardiogram, that required a trained stuff, Impedance cardiography (ICG) is a non-invasive, cheapest and very easy to manipulate. To contribute in this domain we aim to study the performence of a new way of processing for bipolar configuration technics, Knowing that this configuration leads to a no totally perfect acquisition. In the next rubrics we can see the different steps of the work and the presented results. INTRODUCTION Each IMF represents a part of the original signal components; spread over IMFs respiration, muscles or any other movement’s artifacts but also we have the meaningful part of the signal; the cardiac part of the signal that we detect through the IMFs selection. This selection of significant IMFs was confirmed, by visual inspection for all the frequency spectral density, for all sequences in both positions. Fig.1: Power spectral density of the IMFs, in both position. Significant IMFs in supine position shown by rectangle and those of the standing up position shown by cycle. If we compare the different subplots of figure 1, we found that IMF3 is the strong significant IMFs. Table 1. The table shows the recorded averaging heart rate and the calculated ones. (1) Shows the averaging heart rate in a supine position, (2) shows the averaging heart rate in a standing up position. RESULT AND DISCUTION The ICG signal is like almost physiological signals, present a non-stationarity which is disturbed by body (Breathing, muscular movement, the aorta model) and environment artifacts (external movement, temperature, earth gravity). The other disturbance aside this latters artifacts, is the choice of the processing technic that will detect cardiac event containing in the signal. When the technic of acquisition is weak as our tests it will be a challenge to extract the meaningful part of the ICG signal. In generaly and contrarly to us, a four electrodes configuration is used in almost works with several applications but each of them have theirs inconveniences and advantages. Some works used a breath holding to suppress the breathing artifacts but this method may change the value of the stroke volume (SV). Independent Component Analysis (ICA) is also a technic of processing but this one, have to satisfy a condition and still need study to define if the cardiac and their relative artifacts components could be defined as uncorrelated. One of the most used technics, is the wavelet and the fast Fourier transform (FFT) but this type of physiological signal is better analyzed by the Empirical Mode Decomposition (EMD) technic. This is because some of the natural signals components could be hidden in the Fourier domain and in wavelet coefficients but not in EMD. PROBLEM We are going to evaluate the heart rate variability and the enhancement of the measured signal wave form by applying the proposed algorithm which is divided on three part. The first part, consist on analyzing the components of the studied signal by using the Empirical Mode Decomposition (EMD). In this decomposition (EMD), the signal is decomposed into Intrinsic Mode Functions (IMF) signals. In this way, the second part of the algorithm is the frequency components analysis and the significant IMFs selection. In the third part, we apply a heart rate detection algorithm inspired from Tompkins algorithm with some modified steps to adapt it to the ICG signal processing. The Heart rate results was then validated by using several commercial instruments to perform different signals measured in supine then in a standing up position. These signals are: Electrocardiogram signal (ECG), it was measured using the instrument powerlab 8/35 from ADinstruments and the Blood pressure value was acquired with the Tensoval duo control instrument from Hartmann. For the bioimpedance acquisition, the Eval Board AD5933ebz from analog devices was used. We present the three different steps of the constructed algorithm: Empirical Mode Decomposition (EMD) METHODOLGY In this work, a new algorithm based on the Empirical Mode Decomposition (EMD) was implemented with Matlab and based upon two electrodes Impedance cardiography acquisition using the Eval Board AD5933. The aim of this study is to perform a new technics to enhance the processing of a no totally perfect acquisition such as the mentioned above. The results shows that the performance of the algorithm are acceptable and gives a good accuracy as shown in the heart rate comparison with the commercial devices. However, this study still needs more enhancement by increasing the number of recording signals from a group of persons and develop novel methods for the processing algorithm. And this for more precision, rapidity, less memory consumption and efficiency, also, for more enhancement on the shape of the recorded wave form that still not similar to an ICG fourth electrodes recording, where some important characteristic points could be hidden or missed in the two electrodes acquisition. This, false the calculations of stroke volume and more hemodynamics parameters. CONCLUSION