ABSTRACT: ECG signal includes reading and plotting of

ABSTRACT: Heart Defects are immensely threatful to human beings and can cause
death. Improvements in diagnosis and treatment tools are welcome by the medical
community and have proven to be one of the most useful diagnostic tools for
heart patients, one of it to be mentioned would be the Electrocardiogram (ECG),
which operates by measuring the electrical signals emitted by the heart through
electrodes and records the electrical activity of the heart in exquisite
detail. The automatic ECG processing and classi?cation is an emerging tool for
the cardiologists in medical diagnosis for e?ective treatment. Traditional
technique of visual analysis of ECG is complicated for doctors, time consuming
and requires expertise. Hence, Computer based classi?cation and detection of
diseases can be immensely useful in diagnostics. This project has been inspired
by the need to ?nd an e?cient method for ECG Signal Analysis and Classification
which is simple yet has good accuracy and less computation time. It deals with
the study and analysis of ECG signal processing by means of MATLAB tool
e?ectively for classi?cation and detection of heart defects using Lead-II
Con?guration. Study of ECG signal includes reading and plotting of the ECG
signal, acquisition of real time ECG data, ECG signal ?ltering and processing,
feature extraction and detection of certain parameters, decoding, comparison,
classification of the required features. This enormous amount of information
can be stored in the memory for further correspondence. In this thesis, we ?rst
?nd out the characteristics to classify a Normal ECG and then pass any random
signal to check whether the features or the values determined fall within the
speci?ed range with the ones characterized to be a normal ECG. If it does, then
we classify it as Normal ECG else we classify it as an Abnormal ECG using
Lead-II Configuration.


Electrocardiogram (ECG), Lead-II Con?guration, ECG Processing and Classification,
Heart Defects, Matlab.

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Heart is known to be the most significant organ of
the human body that beats in rhythm to pump the blood in circulation through
the body which results in making the action potentials responsible for the
mechanical events within the heart that generates a certain sequence of
electrical events. Due to contraction and relaxation of the muscle tissue of
the heart, electrical activation begins by the movements of ions which
constitute current throughout the body giving rise to potential differences in

An ECG or EKG (Electrocardiogram) records these
potential differences’ using electrodes attached to the surface of the skin and
measures the electrical activity of the heart recorded by a device external to
the body over the amount of time.

It has been known since 1856 that the heart muscle produces
electrical activity and subsequently that it can be measured to provide functional
status and diagnostic information about the condition of an individual’s
heart.  Since the required measurements
are very low in magnitude, noise can have a great impact on measurements.

The ECG analysis is performed by using signal processing.
Signal processing being the enabling technology encompasses the fundamental
theory, applications, algorithms, and implementations of processing or
transferring information contained in many di?erent physical, symbolic or
abstract formats broadly designated as signals.

The modi?cation and processing is used to maximize
the details of information extraction and further analysis. The ECG technique
is implemented with software to perform a various operations like reading,
decoding and recording a data depending on the computing platforms. Then the
waveform is used to ?nd the rate of heart beat, heart rate, heart rate
variability and any disease which are a?ected by the heart.



or EKG is basically an abbreviation for the
word electrocardiogram (derived from the Greek electro for electric, cardio for
heart, and graph for “to write”) and the German word electrocardiogram.

1901 the device used by Willem Einthoven he invented while working in Leiden, Netherlands,
used the string galvanometer proved to be much more sensitive than both the
capillary electrometer Waller used and the string galvanometer that had been
invented separately in 1897 by the French engineer Clement Ader.

Einthoven’s subjects would immerse each of their limbs into containers of salt
solutions from which the ECG was recorded. The letters assigned by Einthoven to
the various deflections that described the electrocardiographic features of a number
of cardiovascular disorders were P, Q, R, S, and T. Einthoven was awarded the
Nobel Prize in Medicine for his discovery in 1924. Though the basic principles
of that era are still in use today, over the years many advances in electrocardiography
have been made.


1: An ECG Graph Paper Measurement


The study of the ECG signal is extensively used for
identification and analysis of irregularities and heart diseases. Each portion
of the heartbeat produces a totally different deflection on the ECG that
represents a realistic and graphic record of the direction and magnitude of the
electrical activity of the heart.

The sinus (Sino-atrial node) node located near the
entrance of the superior vena cava vein, acts as a generator of the sinus
rhythm that produces the heart frequency at about 60-100 cycles per minute.
This activation is then propagated to the right and left atria muscle tissues. There
is a delay at the atrioventricular node, to allow the ventricles to fill with
blood from atrial contraction. This is then followed by the depolarization propagating
to the ventricles through the Bundle of His and spreads along the Purkinje
fibers. This in turn activates the ventricles that contract and pump blood to
the aorta and to the rest of the body. Finally, depolarization occurs followed
by repolarization and this cycle is repeated. 

A Normal ECG waveform tracing (in Lead-II) has a
characteristic shape and features as mentioned in the table.

Fig 2:
A General ECG Waveform

The table 1 shows the ECG features and descriptions.

Table 1:
ECG Features and their Description




P-waves represent atrial


The PR
or PQ segment is the flat, usually isoelectric segment between the end
of the P wave and the start of the QRS complex. This segment
represents the time the impulse takes to reach the ventricles from the
sinus node.


The time
taken for electrical activity to move between the atria
and ventricles is represented by this interval.


normal Q wave represents septal depolarization and is any initial
downward deflection after the P wave.


R wave represents early ventricular depolarisation and is normally the
easiest waveform to identify on the ECG.


The RR-interval
begins at the peak of one R wave and ends at the peak of
the next R wave and represents the time between two QRS complexes.


first negative deflection after the R wave represents the S wave indicating the late ventricular depolarization.


depolarization of the ventricles is represented by the QRS Complex.


It represents the time
taken for the ventricles to depolarize and
then repolarize.


isoelectric line that represents the time between depolarization and
repolarization of the ventricles (i.e. contraction) represents the ST segment.


The J
point is the junction between the termination of the QRS complex and the
beginning of the ST segment.


The T-wave represents ventricular


isoelectric interval on the electrocardiogram (ECG) is TP segment
that represents the time when the heart muscle cells are electrically silent.


Termed as
the diastolic interval through the ECG.


waves represent re-polarization of the Purkinje fibers that
indicates the last remnants of
the ventricular repolarization. Generally it is 0.05mV and has duration
of 0.1s.



Under the expert guidance of
the doctors and after lots of literature review, it was seen that Lead II is
the most preferred monitoring lead of choice for continuous ECG monitoring.
Mostly monitors show one lead at a time, so it is necessary to choose a lead
that gives as much information as possible. The most commonly used lead is Lead
II which measures the potential di?erence between the right arm and left leg
electrode. Since its appearance in 1910 with Willem Einthoven’s invention of
the electrocardiograph, Lead II has traditionally been the most commonly used
monitoring lead.

Fig 3: The Einthoven’s

Paramedics are trained how to interpret rhythms in
lead II and have traditional exams wherein they have established a paradigm of
lead II monitoring in patients. The placement of electrodes for Lead-II
con?guration is located near the apex of the heart due to its best view. It is
the most useful lead for detecting cardiac arrhythmias as it lies close to the
cardiac axis (the overall direction of electrical movement) and allows the best
view of P and R waves.



In the morphology of ECG signal where the normal
rhythm of the heart represents no disease or disorder is called Normal sinus
rhythm (NSR). ECG arrhythmia can be defined as a condition in which the
electrical activity of the heart is irregular and can cause heartbeat to be
slow or fast. The heart rate of NSR is generally defined by 60 to 100 beats per
minute in a normal resting person.

Arrhythmia could be of many types and can be
classified with respect to three factors:

Regularity (Regularly, Irregular and Irregularly, Irregular )

Rate (Abnormal Heart Rhythms)

Origin (Supraventricular and Ventricular)

a resting heart beats at a rate of 100 or more beats per minute in an average
adult, this would represent abnormal rapid beating of the heart defined as Tachycardia
resulting in a drop of pumping efficiency, adversely affecting perfusion.

Bradycardia is defined as a resting heart rate below
60 beats per minute and can adversely affect vital organs.

Arrhythmia can take place in a healthy heart having
minimal consequence, but may also indicate a serious problem that leads to
stroke or sudden cardiac death, scarring of heart tissue or change of heart
structure or heart blocks or premature beats. Depending upon the type of
symptom the arrhythmia would be classified.


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