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.

ECG 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 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

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