Classification of Electrocardiogram (ECG) Waveforms for the Detection of Cardiac Problems By Enda Moloney.

Classification of Electrocardiogram (ECG) Waveforms for the Detection of Cardiac Problems

By Enda Moloney

Contents

Project aims The Heart & ECG ECG Signals MIT-BIH arrhythmia Database QRS Detection Pan-Tomkins Algorithm Artificial Neural Network Timeline Question

Project Aims

Analyse ECG waveform to detect abnormalities Using sample waveform from MIT-BIH database Process waveforms to make it easier to classify them Extract information from ECG waves e.g. QRS

complex Use the artificial Neural Network to classify the ECG

waves into different classes Translate the ECG classification system from Matlab

to C Possible development of a suitable of

hardware/software system and Database

Heart & ECG

Determining if the heart is performing normally or suffering from abnormalities e.g. skipped heartbeats.

Indicating previous damage to the heart muscle.

Providing information on the physical condition of the heart.

Been used to detect non-cardiac diseases

ECG Signal

An ECG is measuring the electrical potential between various points of the body using leads. The normal ECG wave is composed of

The P wave QRS complex The T wave

The relationship between P waves and QRS complexes helps distinguish various

cardiac irregularities.

MIT-BIH Arrhythmia Database

This is a waveform of the data 101 of the MIT-BIH Database of ECG waveforms

Using matlab programme is used to extract information for the MIT-BIH arrhythmia database.

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281111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111

Time / s

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tage

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ECG signal 101.dat

ECG signal 101.dat

0 10 20 30 40 50 60 70 80-1

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281111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111111

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VECG signal 101.dat

QRS Detection

The QRS complex is the most important complex in the ECG. The duration and amplitude sure be measure as accurate as possible.

There are two methods:

the Pan-Tompkins algorithm

the derivation-based method.

Pan-Tompkins algorithm

Pan-Tompkins algorithm proposes a real-time QRS detection algorithm based on slope, amplitude and width of the QRS complexes

After Squaring

0 0.5 1 1.5 2 2.5 3

x 104

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After the implementing the Bandpass filter & differentiation this suppresses P and T waves.

Squaring makes all the results positive and emphasising from large differences arising for the QRS complexes

Artificial Neural Network

ANN is an adaptive system that changes its structure based on external or internal information that flows through the network during the learning phase

When the ECG waves have been processed, they must be classified into Two classes Normal Abnormal

Timeline

30-Jan-09 Transfer the ECG system from Matlab to C, as a

real-time Implementation. The neural network needs to be in C.

15-Feb-09 Develop hardware circuit to interact with the

software, thus a circuit that has a ECG sensor 9-Mar-09

Investigate possible extensions of the system. Eg. Web-based database system that could be used story cardiology records and analysis

Question