ECG Signal Processing
Ojasvi Verma
121852
M.Sc Communicative Electronics
IEM3220 Physiology and Engineering
May 3, 2013
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Overview
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What is an ECG?
Overview of the ECG procedure
How does the ECG work?
Why perform an ECG?
Interpretation of the ECG
Quality of the ECG
Rate, Rhythm, Axis
ECG wave
Signal Acquisition
 Algorithms for ECG Signal Processing
 ECG Digital Filters
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ECG baseline wander
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Heart Rate Data Algorithm
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Autocorrelation function of energy signal
Threshold of energy signal
Application of designed algorithm
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Results
Further work
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??Simple physiology??
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What is an ECG?
Electrocardiography (ECG) is a transthoracic interpretation
of the electrical activity of the heart over a period of time,
as detected by electrodes attached to the surface of the skin
and recorded by a device external to the body.
An ECG is used to measure
- the rate and regularityof heartbeats as well as
- the size and position of the chambers,
- the presence of any damage to the heart and
- the effects of the drugs or devices used to regulate the heart.
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Overview of the ECG Procedure
GRIP – Greet, report, identify, introduce, procedure, privacy, permission.
 Lay patient down.
 Expose chest, wrinkles, ankles.
 Clean electrode sites.
 Apply electrodes.
 Attach wires correctly.
 Turn on machine - calibrate to 10 mm/mV, rate at 25 mm/s.
 Record and print.
 Label the tracing - Name, DoB, hospital number, date and time.
 Disconnect if adequate and remove electrodes.
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How does ECG work?
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Electrical Pulses picked up by the placing electrodes
on patient.
The voltage change sensed by measuring the ??current??
change across two electrodes – a positive electrode and
a negative electrode.
If the electrical impulse travels toward the positive
electrode this results in a positive deflection.
If the pulse travels away from the positive electrode
this results in a negative deflection.
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Why perform an ECG?
It’s part of the admission bundle.
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indicated by the patients symptoms
- symptoms of IMD/MI.
- symptoms associated with dysrhythmias.
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indicated by the patients findings
- cardiac murmur.
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Interpretation of the ECG
Quality of ECG?
 Rate
 Rhythm
 Axis
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P wave
 PR interval
 QRS interval
 QRS morphology
 Abnormal Q waves
 ST segment.
 T wave
 QT interval
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Quality of the ECG
Patient Name
 Date of the ECG
 Is there any interference
 Is there electrical activity from all 12 leads.
 Calibration:
- speed: 25 mm/second
- height: 1cm/mV
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Rate , Rhythm , Axis
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Rate is either
- normal
- bradycardic
- tachycardic
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Rhythm
- are there P waves?
- are they regular?
- does one precede every QRS Complex?
- regular vs irregular
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Axis
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Axis ???
Positive in I and II = NORMAL
Positive in I and negative in II = LAD
Negative in I and positive in II = RAD
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ECG wave
The normal ECG composed of
- a P wave,
- a QRS complex, and
- a T wave.
The P wave represents atrial depolarization.
The QRS complex represents ventricular depolarization.
The T wave reflects the phase of rapid repolarization of
the ventricles.
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Signal Acquisition
ECG signal for digital signal processing and heart rate
calculation acquired by measurement card with sampling
frequency fs = 500 Hz.
Analog signal pre-processing was done on simple amplifier
circuit designated for ECG signal measurement.
The signal was used as an input signal for the digital filters
and the heart rate detection algorithms designing
and testing.
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Algorithms for ECG signal processing
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ECG Digital Filters
Noise elements filtering and baseline wander elimination
with digital filters.
The main noise elements are power supply network 50 Hz
frequency and breathing muscle movements.
These artefacts have to be removed before the signal is used
for next data processing like heart rate frequency
determination.
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ECG baseline wander
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Heart Rate data Algorithms
Algorithms compute heart rate frequency from the signal
energy.
The signal energy was pre-processed in preceding part.
All three described algorithms were used on same signal.
It means it is possible to compare the results and to
choose the best one.
a. Autocorrelation function of Energy Signal.
b. Threshold of energy signal.
c. Peak detection in energy signal envelope.
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Autocorrelation function of energy signal
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Threshold of energy signal
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Applications of designed Algorithm
The designed algorithms were applied to compute heart rate
frequency from ECG signals which were measured during
stress tests.
ECG signal was certainly filtered by digital filters.
The heart rate frequency was computed in frames of signal
with length of 4 s which were 2 s overlapped.
The division of signal to frames simulates real-time
processing which will be used in microprocessor
implementation.
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Results
The designed digital filters and the heart rate frequency
algorithms are very simple.
The filters have small order. It saves the computing time,
but it is very effective for processing the ECG signal.
It is the reason why these algorithms could be easily
implemented to microprocessor unit.
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Further work
In future healthcare, wireless sensors can be integrated into
"smart clothes", monitoring the health status of a patient
continuously.
For hearth-diseases, a mobile electrocardiogram (ECG)
can be worn that detects abnormalities automatically and
transmits this information to the patient's smart phone
or to a hospital.
Thanks
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