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

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

• By Enda Moloney

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Contents

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

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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

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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

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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.

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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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ECG signal 101.dat
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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.

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Pan-Tompkins algorithm

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

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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

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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

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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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Question