PRESENTATION ON IMPLEMENTATION OF ALGORITHM FOR DIAGNOSIS OF ECG WAVEFORM USING MATLAB. PRESENTED BY: NAGESHWARI AGARWAL NIDHI BHUTANI ABHIJEET BODHANKAR ABHISHEK ARORA GUIDED BY: Mr. ANURAG SHRIVASTAVA Sr. Lecturer EI Department

INTRODUCTION OF ECG The electrical potentials generated by the heart appear throughout the body and on its surface. The potential differentials are determined by placing electrodes on the surface of the body and measuring the voltage between them. The ECG records and compares the electrical activity detected in the different electrodes and the result obtained is called “lead”. The ECG signal is characterized by six peaks and valleys labeled with different characters: P, Q, R, S, T and U

The conventional ECG systems record changes in electrical activity by drawing a trace on a moving paper strip (Berbari, 2000). However, these charts must be interpreted by the physicians. Nowadays, ECG systems for self-diagnosis are very primitive, expensive and not reliable. Therefore, the proposed system is a step further in the ECG analysis, as it allows self-diagnosis in the complete ECG signal and it is a low-cost system.

GENERATION OF REAL TIME ECG

ECG WAVEFORM

ECG WAVEFORMS P WAVEElectrical activation (depolarization) of the right then left atrium due to discharge from the SA (sinoatrial) node. PR SEGMENTPassage of the impulse through the atrioventricular (AV) node and bundle of HIS QRS COMPLEX Electrical depolarization of the ventricles ST SEGMENTPlateau phase T WAVERepolarization of the ventricle U WAVERepolarization of the HIS purkinje fibres.

METHODOLOGY

ECG GENERATION Start Select input 1= Predefined 2=User defined Is input =1? Set default values Enter heart rate Enter specifications for P wave, q wave, r wave, s wave and t wave Display the ECG wave Stop Yes No

DISEASE DETECTION Start Select ECG Sample Separate and measure P wave Separate and measure R wave The measured values of P and R wave are compared with standard values. On the basis of comparison the disease is detected Stop

FUNCTIONING

G ENERATION OF ECG We have developed algorithm for generating ECG waveform using simulation technique. The parameters of ECG can either be selected as default values i.e. for normal ECG or user defined values can also be selected. The parameter includes heart rate and amplitude and duration of P, Q, R, S & T waves. This simulated ECG’s are considered as sample waves for further investigation of diseases.

G ENERATED E CG

H OW TO DETECT DISEASE From the selected simulated ECG sample, we are separating P wave and R wave. The separation of respected waves is done by using looping concept. By measuring the amplitude of P and R wave, we are comparing this values with the standard values. Then by using this values we will detect the disease which lead to formation of given ECG.

S EPARATED P W AVE Amplitude of P wave is determined by using MATLAB functions. Amplitude of P wave for shown fig. is mV.

S EPARATED R WAVE Amplitude of R wave is determined by using MATLAB functions. Amplitude of P wave for shown fig. is mV

DISEASES

N ORMAL ECG AMPLITUDE OF P WAVE0.25 mV AMPLITUDE OF R WAVE1.60 mV

S INUS B RADYCARDIA AMPLITUDE OF P WAVE0.2 mV AMPLITUDE OF R WAVE1.88 mV

S INUS B RADYCARDIA WITH AV B LOCK AMPLITUDE OF P WAVE0.2 mV AMPLITUDE OF R WAVE1.88 mV

J UNCTIONAL R YTHUM AMPLITUDE OF P WAVE0.24 mV AMPLITUDE OF R WAVE2 mV

S INUS R YTHUM WITH P AUSE AMPLITUDE OF P WAVE0.25 mV AMPLITUDE OF R WAVE1.60 mV

P AROXYSMAL S UPRAVENTRICULAR T ACHYCARDIA AMPLITUDE OF P WAVENone AMPLITUDE OF R WAVE1.96 mV

CONCLUSION AND FUTURE SCOPE

CONCLUSION The theme of the project when merged with all possible parameters of an ECG can give result a fantastic automated system which will give the details from which a person is suffering rather giving any graphical representation of data, which will be a great success in the field of diagnostics.

FUTURE SCOPE In above algorithm we have used only P and R wave for disease detection, the scope of this project can further modified by using other parameters i.e. measurement of heart rate, PR interval, QRS interval and amplitude of remaining other waves for disease detection. The project can be extended for implementation of same algorithm for real time ECG waveforms for diagnosis and to detect the disease. The interference of Noise can also be considered and thus removal of noise can be done.

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