Comparison of Different ECG Signals on MATLAB

Transcription

1 International Journal of Electronics and Computer Science Engineering 733 Available Online at ISSN Comparison of Different Signals on MATLAB Rajan Chaudhary 1, Anand Prakash 2, Chandan Gupta 3 Department of Electronics and Communication Engineering 1, 2, 3 Invertis University, Bareilly, India 1 rajanchaudhary12@gmail.com 2 anand.anandprakash@gmail.com 3 chandan.g@invertis.org Abstract- In this paper we discuss about biomedical engineering and then a brief description of signal. We have generated a new method to compare different arrhythmic heart signals with normal sinus signals at MATLAB. This is making the comparison very easy. is used to measure the rate and regularity of heartbeats, as well as the size and position of the chambers, the presence of any damage to the heart, and the effects of drugs or devices used to regulate the heart, such as a pacemaker. Most s are performed for diagnostic or research purposes on human hearts, but may also be performed on animals, usually for diagnosis of heart abnormalities or research. Result obtained showing that Comparison of Normal (Sinus) and Abnormal (arrthymia) signal. Through this method we can compare any type of disordered signal of heart. Keywords- ; electrodes; R-Wave detection; simulation; MATLAB I. INTRODUCTION Biomedical engineering is the application of engineering principles and design concepts to biology and medicine. This field developing to narrowing the gap between engineering and medicine. It aggregates the design and problem solving skills of engineering with medical and biological sciences to advance healthcare treatment, including diagnosis, monitoring, treatment and therapy. Biomedical engineering has further branches within biomedical engineering like biomedical electronics, biomechatronics, cellular, tissue and genetic engineering, neural engineering. Biomedical engineering has a branch which includes the measurement of physiological variables and parameters are known as biometrics. Biomedical engineering can generally be classified into two major categories: clinical and research. Clinical engineering is basically related to the diagnosis, care and treatment of patients and research engineering is devoted in the search for new knowledge pertaining to the various systems that compose the human organism. Clinical instruments handled by the physician or nurse, whereas research instruments are generally operated by skilled technologists whose primary training is in the operation of such instruments. II. DESCRIPTION OF VARIOUS TERMS Electrocardiogram is a test that measures the electrical activity of the heart. The heart is muscular organ that beats in rhythm to pump the blood in circulation through the body. Electrocardiograph is an instrument used in the detection and diagnosis of heart abnormalities that measures electrical potentials on the body surface through electrodes and generates a record of the electrical currents associated with heart muscle activity. Electrocardiography is a noninvasive procedure for recording changes in the heart activity. It is a starting point for detecting and analyzing many cardiac problems, including angina pectoris, heart disease, arrhythmias, tachycardia, bradycardia etc. A. Polarization- If cardiac cell at rest meaning no electrical activity takes place. B. Depolarization- Cells generates an electrical impulse, this electrical impulse causes the ions to cross the cell membrane and causes the action potential. C. Resting Potential-Different concentrations of ions, such as sodium, potassium and calcium, is separated by the cell membrane of the cardiac muscle cell.

2 Comparison of Different Signals on MATLAB 734 Figure 1. Change in Electrical Polarity Figure 1.shows the change in electrical polarity of the cell membrane opens ion-channels. D. Repolarization- It is the return of the ions to their previous resting state, which lead to the relaxation of the myocardial muscle. E. electrodes- By external electrodes electrical activity going through the heart can be measured. The electrocardiogram registers these activities from electrodes which have been attached onto different places on the human body. 12 leads are calculated using 10 electrodes. III. RHYTHMS The primary function of the heart is to circulate and supply blood and nutrients to the body. The regular beating or contraction of the heart moves and transfers the blood throughout the body. Each heart beat is controlled by electrical impulses travelling through the heart. In the normal heart these electrical impulses occur in regular intervals (time period). When something goes wrong with the electrical system of the heart, rhythms does not beat regularly and rhythm disorder takes place. Figure 2. Representation of normal

3 IJECSE, Volume2, Number 2 Rajan Chaudhary et al. 735 P wave during normal atrial depolarization, the main electrical vector is directed from the SA node towards the AV node and spreads from the right atrium to the left atrium inside the heart. From the beginning of the P wave to the beginning of the QRS complex PR interval is measured. The PR interval reflects the time the electrical impulse takes to travel from the sinus node through the AV node and entering the ventricles inside the heart. QRS complex reflects the rapid depolarization of the right and left ventricles. The QRS complex usually has much larger amplitude than the P wave, as they have large muscle mass compared to the atria. The QRS complex and the T wave is connected by ST segment. The period when the ventricles are depolarized is represented by the ST segment. The repolarization of the ventricles is represented by the T wave. The interval between the beginnings of the QRS complex to the apex of the T wave is referred to as the absolute refractory period. U wave is hypothesized to be caused by the repolarization of the interventricular septum. They normally have low amplitude and even more often completely absent. They always follow the T wave and also follow the same direction in amplitude. If they are too prominent, suspect hypokalemia, hypercalcemia etc. [1-3]. Heart rates in Adults: Normal beats/min. Tachycardia- greater than 100 beats/min. Bradycardia- lesser than 60 beats/min. Heart rates in Children: New Born bpm 2 years bpm 4 years bpm 6 years bpm Figure 2 shown above is normal sinus rhythm. IV. ABNORMALITIES IN recordings can be used as a diagnostic tool to determine abnormalities in cardiac function or it can be visualize the effects of cardiac tissue damage. Abnormalities in the QRS complex indicate problems in the ventricles or ventricular conduction. In normal, T wave is of positive amplitude but in abnormal, the T wave can be inverted having negative amplitude. There are various abnormal and some we discuss here: i. Sinus Bradycardia Bradycardia is a term to describe the heart beating more slowly than normal. Sinus bradycardia can occur in well-conditioned athletes and during sleep relaxation. In the case of athletes, the heart muscle is tremendously strong and efficient at pumping blood, therefore, less contraction needed. During deep relaxation, the body is at rest and requires less oxygen consumption than during normal activity which allows the heart rate to slow. However, sinus bradycardia can also occur as a result of heart disease or as a reaction to medication. ii. Sinus Tachycardia Figure 3. Sinus bradycardia

4 Comparison of Different Signals on MATLAB 736 Excessive heart rate above 100 beats per minute (BPM) which originates from the SA node. Causes include stress, fright, illness and exercise. It is essential to identify one P for each QRS. It may be difficult to differentiate a sinus tachyarrhythmia from an atrial tachyarrhythmia [4]. Figure 4. Sinus Tachycardia iii. Atrial Flutter Atrial flutter is a condition where there are multiple atrial contractions for every ventricular contraction. It is caused by a single large electrical signal that propagates around the atria. The rate of atrial contraction can be between 200 and 350 beats per minutes. The amount of blood being pumped by the atria can be very small as a result of one side of the atria being contracted while the other being relaxed. The electrical signals enter the AV node at a rate that is too rapid to create a ventricular contraction for every atrial contraction. As a result, there are multiples P-waves in the for every QRS-T complex. Figure 5. Atrial flutter iv. Ventricular Flutter In this cardiac arrhythmia, the verticals can be paced at more than 200 beats per second. This can be triggered by an extrasystole or ectopic pacemaker that occurs in the ventricles. The pumping of blood becomes extremely inefficient. There is no visible P wave in the recording and the QRS complex and T wave are merged in regularly occurring waves with a frequency between 180 to 250 beats per minute [5].

5 IJECSE, Volume2, Number 2 Rajan Chaudhary et al. 737 Figure 6. Ventricular Flutter V. RESULT In this paper, we compared the amplitude of Normal signal and abnormal signal on MATLAB which tells us about the amplitude of signal and abnormal signal. 3 NORMAL Heart Rate Data TIME Figure 7a. Normal signal

6 Comparison of Different Signals on MATLAB ABNORMAL Heart Rate Data TIME Figure 7b. Abnormal signal 2 STRESS Data TIME Figure 7c Stress condition signal Figure 7. Comparison of Normal (Sinus) with Abnormal (arrhythmia) and Stress condition signal. From the Fig. 7, in Fig. 7b the QRS peak is very small and of Fig. 7c is also smaller than Fig.7a. So this thing shows that the signal of Fig.7b and Fig.7c is not normal. The amplitude of P wave in Normal signal is mv at msec and amplitude of Abnormal signal is -0.5mV and it is -0.95mV at same time in Stress condition, these things shows that Fig.7b and Fig.7c are abnormal signal. In stress condition heart rate may increase or decrease, here we are taking decreased condition [6].

7 IJECSE, Volume2, Number 2 Rajan Chaudhary et al. 739 TABLE 1 COMPARISION OF DIFFERENT SIGNALS Heart Rate Sampled at Time (in msec.) (mv) NORMAL ABNORMAL STRESS In Table 1, conditions of different signals are compared. Data is for one minute, peak value (R) of signal is in mv at Time in msec, whose value of sample is shown. As it is clearly compared the difference, the first peak of Normal is at msec, Abnormal is delayed at msec and more delayed at in Stress condition. Similarly it can be easily comparable for other peak values [7-8]. VI. CONCLUSIONS The paper presents an original work related to comparison of Signals. Simulation of dynamical systems is one of the challenging computational tasks because of its numerical complexity and simulation time The simulation has been done in MATLAB for various sets of inputs such as normal (sinus), bradycardia, tachycardia, stress condition of signals. Some results and discussions are clearly exposed. The implication of this research may be helpful for scientific researchers in the area of signals processing. So, cardiac patient can be identified by finding his energy levels and comparing them with that of a normal person. This method can be used to identify other heart disorders also. For all the results obtained in this work, we used the MATLAB programming environment. It works well to maintain the original signal and has important practical value. The reference signal were created using a predefined authentic source. REFERENCES [1] N. Kumar, I. Ahmad and P. Rai, Signal Processing of on MATLAB, International Journal of Scientific and Research Publications, Vol.2, Oct [2] T. J. Sullivan, S.R. Deiss and G. Cauwenberghs, A Low-Noise, Non-Contact EEG/ Sensor, Biomedical Circuits and Systems Conference, BIOCAS IEEE, [3] A.D. Jeyarani and T. Jaya Singh, Analysis of Noise-Reduction Techniques on QRS Waveform- by applying Different Filters, IEEE, [4] B.R. Shankara Reddy, Paul E. Elko, Dave W. Christenson, and G. Ian Rowlandson, Detection of P Waves in Rerrting : A Preliminary Study, IEEE, [5]. C. Saritha, V. Sukanya, Y. Narasimha Murthy, Signal Analysis Using Wavelet Transform, Bulg. J. Phys, [6] [7] Rangaraj M. Rangayyan, Biomedical Signal Analysis: A Case Study approach, IEEE press, wiley-inter science, John wiley and sons, Inc.2002 [8] Gari D. Clifford, Francisco Azuaje and Patrick McSharry, Advanced methods & tools for Data Analysis Artech House Publishers -Sep 2006.