Electro Physiology of the Human Heart

Introduction

This chapter is the first chapter in the thesis which gives introduction of the present study. The chapter defines electro physiology of human heart, blood circulation in both pulmonary and systemic in detail, the components in cardiovascular system and heart sounds. It explains in detail the generation of potential due to mechanical activity of human heart and sounds produced due to closure of valves during blood pumping from atrias to ventricles and to respective parts of the body. This chapter presents a detailed survey on literature focusing on different methods to measure and analyse ECG and PCG.

Electricity plays an important role in medicine. The control and operation of nerves, muscles and organs are functioning by the electricity generated inside the body. The forces of muscles, the action of brain and all nerve signals to and from the brain are caused by the attraction and repulsion of electrical charges. Many electrical signals are generated to carry out the special functions of the body. These signals are the result of electrochemical action of certain type of cells. The best known signals are electrical potentials of nerve transmission and the electrical signals observed in electromyogram (EMG) of the muscle, the electrocardiogram (ECG) of the heart and the electroencephalogram (EEG) of the brain.

One means of obtaining diagnostic information about muscles, heart and brain are to measure their electrical activity. The record of the potential from muscles during movement of is called the electromyogram (EMG). The rhythmical action of the heart is controlled by an electrical signal initiated by spontaneous stimulation of pacemaker cells located at apex of the right atrium i.e. sinoatrial node (SA node). The recording of heart’s potentials on skin is called electrocardiogram (ECG). The recording of the electric signals due to electrical activity of neurons in the cortex of the brain is called electroencephalogram (EEG). The present study is to study the electrical activity of heart during its mechanical vibrations.

The primary step in investigations of physiological systems requires the appropriate sensors to transducer the phenomenon of interest into a measurable electric signal. The field of biomedical has advanced to the stage of practical application of signal processing and pattern analysis techniques for efficient and improved non- invasive diagnosis.

1.1 Physiology of Heart and Vascular System

The analysis of variability in cardiovascular signals is applied widely and many experimental setups were put forward. Spontaneous fluctuations can be observed in cardiovascular function, such as heart rate and blood pressure, even when the environmental parameters are maintained at a constant level as possible and no perturbations influences can be identified.

The observations of heart rate fluctuations is related to various cardiovascular disorders, the analysis of heart rate variability has become widely used tool in the assessment of the regulation of heart rate behavior (Timo Makikallo 1998). The study of cyclic variations of heart rate plays an important role in the assessment of both physiological and clinical aspects (Narayana Dutt & Krishnan 2000).

The heart is actually two separate pumps. A right heart that pumps the blood through the lungs and left heart pumps the blood through the peripheral organs. Each of these composed of ‘atrium’ and ‘ventricle’. Atrium receives the blood and pumps into ventricles. Ventricles supply the main force that circulates the blood either through pulmonary circulation by the right ventricle or through the systemic circulation by the left ventricle(Fig 1.1)

The blood, blood vessels and heart make up the cardiovascular system (CVS). The blood and its supply of oxygen are so important to the body that the heart is the first major organ to develop in the embryo.

The mechanism in the heart provides cardiac rhythmcity and transmits action potentials through the heart muscle to cause the heart’s rhythmical beat. The cardiac event that occurs from the beginning of the next are called the cardiac cycle. Each cycle is initiated by spontaneous generation of an action potential in the’ Sino atrious node’ or ‘Sinus node’.

The cardiac cycle consists of a period of relaxation called ‘diastole’, during which the heart fills with blood fallowed by a period of contraction called ‘systole’ together is known as a ‘beat’.

The heart is composed of three major types of cardiac muscle; atrial muscle, ventricular muscle and specialized excitatory and conductive muscle fibers. Cardiac muscle is a syncytium of many heart muscle cells which are interconnected with “intercalated discs” which are of actually cell membranes separates cardiac muscle cells from one another and offers low resistance to ions to diffuse through cells. If one of these cells is excited, the action potential spreads to all of them.

The heart is composed of two syncytiums the atrial syncytium that consists of walls of two atria and ventricular syncytium consists of the walls of two ventricles. The atria are separated from the ventricles by tissue that surrounds the atrio-ventricular valvular openings. Potentials are conducted from atrial syncytium into ventricular syncytium through the specialized conductive system called A-V bundle a bundle of conductive fibers.

The division of the muscle of the heart into two functional syncytiums allows the atria to contract a short time ahead of ventricular contraction, which is important for effective heart pumping through lungs and peripheral organs. Another importance of the system is that it allows all portions of the ventricles to contract almost simultaneously, which is essential for most effective pressure generation in the ventricular chambers

The cardiac cells present in the heart tissue are individually surrounded with an insulating membrane (supporting a potential mV) containing selective permeable ionic channels. The currents through these channels interact with the membrane potential to regulate the activity of the cell. The flow of various ions (Na,K,Ca …etc) through out the cardiac tissue is responsible for the propagation of the electrical waves through tissue in turn provides the driving force behind the heart’s mechanical contraction and its ability to pump blood through the body.

1.2. Components of Heart

The heart is a conical, hollow muscular organ placed obliquely behind the body of the sternum and adjoining parts of the body of the costal cartilages, so that 1/3 rd of it lies right and 2/3 rd to the left of the median plane. The heart measures about 12x9cm and weighs 300 gm in males and 250 gm in females.

The human heart has four chambers as shown in fig 1.2. The upper two chambers, the right and left atria are receiving chambers of blood. Atria collects venous blood from the body and about 75% of the blood flows directly into the ventricle even before atrial contraction. The atrial contraction causes an additional 25% filling the ventricles. The heart’s lower chambers right and left ventricles are the powerful pumping chambers. The right and left sides of the heart are separated from each other by a wall of tissue .each side pumps blood through a different circuit of blood vessels.

1.2.1. The Right Atrium

It is the right upper chamber of the heart receives venous blood from the whole body and pumps it to the right ventricle through right atrioventricular (tricuspid) opening. The chamber is elongated vertically, receiving the superior vena cava at the upper end and the inferior vena cava at the lower end. Deoxygenated blood from the whole body feeds into two large veins, the superior vena cava and inferior venecava, which empty into the right atrium of the heart and the same pumps to the right ventricle.

1.2.2. The Right Ventricle

The right ventricle is a triangular chamber which receives blood from the right atrium and pumps it to the lungs through the pulmonary trunk and pulmonary arteries.

Externally, the right ventricle has two surfaces anterior and inferior. The cavity of the right ventricle is crescent in section because of the forward bulge of inter ventricular septum. The wall of the right ventricle is thinner than that of left ventricle in a ratio 1:3.

1.2.3. The left atrium

The left atrium forms the left 2/3 of the base of the heart and is a quadrangular chamber. It receives oxygenated blood from the lungs through four pulmonary veins and pumps it to the left ventricle through Mitral valve.

1.2.4. The Left Ventricle

The left ventricle receives oxygenated blood from the left atrium and pumps it into the aorta, the body’s largest artery. Smaller arteries that branch off the aorta distribute blood to the various parts of the body. It forms the apex of the heart .The cavity of the left ventricle is circular in cross section and has the thickest walls nearly half an inch in an adult because it must work the hardest to propel blood to the farthest reaches of the body.

1.2.5. Valves of the Heart

The valves of the heart maintain unidirectional flow of the blood and prevent blood from flowing backward in the heart i.e. the valves open easily in the direction of blood flow, but when blood pushes against the valves in the opposite direction the valves close.

There are two pairs of valves in the heart i) atrio ventricular valves ii)Semilunar valves. Atrio-ventricular valves are located between the atria andventricles as shown figure. The right atrio-ventricular valve is formed from three cusps of tissue and is called “Tricuspid valve”. While the left atrio- ventricular valve has two cusps and is called “Bicuspid or Mitral valve”. Both valves are made up of a fibrous ring to which the cusps are connected .The cusps are flat and project into the ventricular cavity. The atrio- ventricular valves kept competent by active contraction of the papillary muscles.

Semi lunar valves are located between the ventricles and arteries and each of them consist of three half moon shaped flaps of tissue. They are not attached to fibrous ring but are to the blood vessel .The right semi lunar valve between right ventricle and pulmonary artery is “pulmonary valve ” and the valve between left ventricle and aorta is “aortic valve “.These valves are closed during ventricular diastole.

1.2.6. Superior Vena Cava

It is about 7 cm long venous channel which receives blood from the upper half of the body and empties it to the right atrium like other large veins. It has no valves.

1.2.7. The Aorta

The aorta is the great arterial trunk which receives oxygenated blood from the left ventricle and distribute it all parts of the body.

1.2.8. Myocardium

It is the muscle tissue wraps around a scaffolding of tough connective tissue to form the walls of the heart chamber. The atria the receiving chambers of the heart have relatively thin walls than the ventricles, the pumping chambers.

1.2.9. Pericardium

It is a tough, double layered sac which surrounds the heart. The inner layer of the pericardium is known as epicardium rests on top of the heart muscle. The outer layer is attached to the breast bone and other structures in the chest cavity and helps hold the heart in place. The space between the two layers of the pericardium filled with watery fluid which prevents these layers from rubbing against each other during heart beat.

1.2.10. Endocardium

It is the inner surface of the heart’s chambers lined with a thin white sheet of shiny tissue. The same type of tissue also lines the blood vessels forming continuous lining throughout the circulatory system. The lining helps blood to flow smoothly and prevents clotting of blood in the circulatory system.

The heart is nourished not by blood passing through, but by the blood vessels also known as “coronary arteries” which encircle the heart like a crown.

About 5% of the blood pumped to the body enters the coronary arteries, which branch from the left ventricle .Three main coronary arteries the right , the left circumflex and the left anterior descending nourish different regions of the heart muscle. From these three arteries small branches arise to provide a constant supply of oxygen.

1.3. A Detailed Description of Vascular System

The cardio vascular system is concerned with the transport of blood and lymph through the body. It may be divided into four major components, the heart, the macro circular i.e. blood vessels arteries and veins, micro circular i.e. capillary and lymph vascular system i.e. water and other components of blood plasma. The cardio vascular system (CVS) controls the blood pressure by altering the heart rate and compliance i.e. elasticity of blood vessels. (Isla Gilmour 1995).

1.3.1. Arteries

Arteries transport blood from high pressure to body tissues as their structure permits them to expand and contract under different pressures due to the presence of elastic fibers. The main artery of the heart is “aorta”, which starts from the left ventricle transporting oxygen and nutrients to all body tissues. The presence of elastic fiber enables the arteries to expand when each pulse of blood pumped by the heart and regains its original shape when tension is released.

Like all blood vessels the inner layer of arteries is known as “tunica intima”, composed of a single layer of flattened endothelial cells fitted together to form a smooth, continuous tube. In large arteries the same layer is supported by thick band of elastic fibers. The middle layer is known as “tunica media” consisting of smooth muscle and elastic fibers. In very large arteries the outer layer is known as “tunica adventitia” also contains elastic fibers and connective tissue.

1.3.2. Veins

Veins transport deoxygenated blood at low pressure toward the heart and act as reservoirs of different capacities to maintain a steady return of blood to heart. The veins of systemic circulation terminate at body’s largest veins superior and inferior vena cava which empty into the right atrium of the heart.

The walls of the veins are thinner and contain little elastic fiber with greater internal diameter. These structural properties help them to stretch and store the blood. Since the pressure in veins is low some structural changes is needed to prevent blood from downward pull of gravity. The veins in the lower body contain special one-way valves prevent the accumulation of blood in the legs and feet.

During exercise the muscles are in extremities, relaxing and contracting alternately squeezing the veins to force the blood upward towards the heart. The tunica media of veins is thinner and contain less elastic fiber and smooth muscle to function at low pressure and serving as reservoirs to maintain a steady return of blood to the heart.

1.3.3. Arterioles

The functions of arterioles are to distribute the blood and pressure reducing valves. They play an important role in determining the blood pressure. The arterioles have smooth muscle in their walls and do not stretch rather act as pressure reducing valves between the arteries and capillaries. They prevent delicate capillaries from high pressure of blood in the arterial system.

The degree of muscular tension in the walls of arterioles decides their internal diameter in turn changes the resistance of blood flow in arterioles. As they affect the blood pressure because they account for a large component of the peripheral resistance to blood flow. Blood pressure is the product of total peripheral resistance and cardiac output.

1.3.4. Venules

The function of venules is to drain blood from the capillary bed into the venous system.

1.3.5. Capillaries

Capillaries are very small blood vessels their diameter ranges from 4-15 μm.

The sum of the diameters of all capillaries is significantly larger than that of the aorta which results in decrease of blood pressure and flow rate. Capillaries are composed of a single layer of flattened endothelial cells fitted together to form a continuous tube. This results in a very large surface to volume ratio. The low rate of blood and large surface area facilitate the functions are:

• Providing nutrients and oxygen to the surrounding tissue.
• The absorption of nutrients, waste products and carbon dioxide and
• The execution of waste products from the body.

1.3.6. Lymphatic Vessels

Parts of the blood plasma will execute from the blood vessels into the surrounding tissues because of transport across the endothelium. The fluid entering tissues from capillaries adds to the interstitial fluid normally found in the tissue. The surplus of liquid will return to the circulation .Lymph vessels are dedicated to this unidirectional flow of liquid, the lymph. The lymph vessels can be divided into three types depending on their shape and size.

Lymph Capillaries

These are larger than blood capillaries and very irregular on shape. They begin as blind ending tubes in connective tissues.

Lymph Collecting Vessels

They appear almost similar to lymph capillaries but a bit large and form valves. The lymph is moved by the compression of the lymph vessels by surrounding tissues. The direction of lymph flow is determined by the valves

Lymph Ducts

They contain one or two layers of smooth muscle cells in their wall and form valves. The walls of lymph ducts are less elastic and during contractions contribute to the movement of lymph towards the heart in addition to the compression of the ducts by surrounding tissues.

1.3.7. Relations to Other Systems and Organs

The heart and vascular system perform almost the same function to provide oxygen, nutrients and harmonic to the cells of the body tissue. They can be considered as one unit rather than two, because each is equipped to carry out half of that function.

The vascular system is also closely related to the adrenergic receptors and the autonomic nervous system, which together control important aspects of its function.

The alpha adrenergic receptors are the smooth muscle cells in arteries, veins, arterioles and venules. These receptors bind molecules released by cells of the autonomic nervous system and respond by contracting.

1.4. Blood Circulation -Systemic and Pulmonary

The heart basically a double pump provides the force to circulate the blood through two major circulatory systems, the pulmonary circulation in the lungs and the systemic circulation is in organ system that transports substances to and fro from cells. The blood in normal individual circulates through one system into before being pumped by the other part of the heart to the second system.

The heart is a muscle composed by cells containing small filaments of actin and myosin. These proteins interact in the sense of forming actomyosin during muscle contraction, thus leading to the main purpose of the heart: pumping the blood through the circulatory system (Manuel Duarte Ortigueiva 1959). The synchronous nature of contraction of heart results in the efficient pumping of blood through the pulmonic and systemic circulation (J.Olansen et al 2000).

The circulatory system can be thought of as a closed loop circulation system with two pumps. One way valves keep the flow downward through the pumps.

1.4.1. Systemic Circulation

The heart ejects oxygen rich blood under a pressure about 125 mm Hg from main pumping chamber left ventricle, through the largest artery the aorta. Subdivided into smaller arteries in turn divided into even smaller arteries called arterioles and finally into a very fine meshwork of vessels called the capillary bed.

Capillaries permit to dissolve oxygen and nutrients from the blood to diffuse across the fluid, known as “interstitial fluid” that fills the gaps between the cells of tissues of organs. The dissolved oxygen and nutrients enter cells through interstitial fluid by diffusion across the cell membranes.

Mean while carbon dioxide and other wastes leave the cell diffuse through the interstitial fluid, cross the capillary bed and enter the blood. The blood collects in small veins called venules gradually join together to form progressively larger veins. Finally the veins converge into two large veins, the superior vena cava and the inferior vena cava bringing blood from upper half and lower half of the body respectively. Both of these main veins join at the right atrium of the heart.

1.4.2. Pulmonary Circulation

The deoxygenated blood returning from the organs and tissues of the body stored momentarily in the reservoir i.e. right atrium, during weak contraction (5 to 6 mm Hg) the blood pushed into the right ventricle. On the next ventricular contraction this blood is pumped at a pressure of about 25 mm Hg through pulmonary arteries to the capillary system in the lungs.

At this site microscopic vessels pass adjacent to the “alveoli” or air sacs of the lung where it exchanges oxygen from the membrane to the blood and leaves carbon dioxide from blood to the same membrane. The freshly oxygenated blood then travels through the main veins from the lungs into the left reservoir i.e. left atrium of the heart. During weak arterial contraction (7 to 8 mm Hg) blood enters the left ventricle.

On the next contraction of the left ventricle sends blood to the aorta and then to general circulation. On average a typical adult has about 4.5 lts of blood and each section of the heart pumps about 80 ml in each contraction. About 30 sec to 1 min is needed for the average red blood cell to complete a full circuit through both the pulmonary and systemic circulation.

The blood volume is not uniformly divided between the pulmonary and systemic circulation. At any one time 80% of the blood is in the systemic circulation and 20% is in the pulmonary circulation. Of the blood in the systemic circulation about 15% is in the arteries, 10% is in the capillaries and 75% is in the veins. In the pulmonary circulation about 7% of the blood is in the pulmonary capillaries and the remaining is almost equally distributed between the pulmonary arteries and pulmonary veins.

1.4.3. Additional Functions

In addition to oxygen, the circulatory system also transports nutrients derived from digested food to the body. These nutrients enter the blood from the walls of the intestine carries the nutrients to the liver for farther metabolic processing.

The liver stores variety of substances such as sugar, fats and vitamins and releases glucose to the blood as needed. The liver also cleans the blood by removing waste products and toxins. After the blood is cleaned, enter the veins converge to form the large vein that joins the vena cava at right atrium.

The circulatory system plays an important role

* In regulating body temperature

* To collect chemical messengers called hormones from hormone producing glands and transports to specific organs and tissues to regulate body’s rate of metabolism, growth, sexual development and other functions.

* With immune system and coagulation system, the immune system is a complex system of many disease fighting white blood cells and anti bodies circulate in the blood and are transported to sites of infection. The coagulation system is composed of special proteins called clotting factors which circulate in the blood. When ever blood vessels are cut to torn, the coagulation system works rapidly to stop the bleeding by forming clots.

Other organs support the circulatory system are the brain and the parts of nervous system constantly monitor blood circulation, sending signals to the heart or blood vessels to maintain constant blood pressure.

New blood cells are produced in the bone marrow and old blood cells are broken down in the spleen, where iron and other minerals are recycled. Metabolic waste products are removed from the blood by kidneys which also screen the blood for excess salt and maintain blood pressure and to maintain blood pressure and to balance minerals and fluids of the body.

1.5. Heart Diseases

Heart disease has become very common nowadays due to changes in life style. Many of these diseases are due to either increase the work load of heart or reduce the ability to work at normal rate.

1.5.1. Tachycardia

There are many factors that are responsible for development of heart disease. One such factor is “High blood pressure” (Hypertension) which causes the muscle tension to increase in proportion to the pressure. A fast heart rate (Tachycardia) increases the work load.

1.5.2. Heart Attack

The heart disease that causes most deaths is “heart attack”. A Heart attack is caused by blockage of one or more arteries to the heart muscle. During and after heart attack the ability of the heart is seriously impaired. Bed rest and giving oxygen reduces the work load on heart which increases the oxygen content in the blood so that blood pumped by the heart will be less. Alternate method to reduce risk of heart attack is the regular exercise program which opens alternate routes in cardiovascular system.

1.5.3. Congestive Heart Failure

Another common disease is congestive heart failure which is due to enlarge in size of the heart reduce the ability for adequate blood circulation.

Applying law of Laplace, if the radius of the heart is doubled, the tension of the heart muscle should be doubled which in turn reduces the efficiency of the heart muscle to maintain the same blood pressure.

Since the heart is stretched it may not be able to produce sufficient force to maintain normal circulation. Stretched heart muscle is less efficient than the normal. It consumes much more O2 for the same amount of work.

1.5.4. Bradycardia

Patients with inadequate electrical signal in the heart muscle will affect the work load of heart. The artrioventricular node i.e. between Atria and Ventricles is fatty and does not conduct electric signal and ventricle receive no signal from Atria, but being natural pacing centers which provide a pulse. The resulting heart rate is 30 beat/min i.e. Bradycardia results semi invalidism.

1.5.5. Pace Makers

If heart’s electrical signals are inadequate to stimulate heart muscles, artificial pace makers are available. To improve the quality of life of faulty atrioventricular nodes, artificial pacemakers are developed.

The pacemaker contains a pulse generator that put out 72 beats / min. The pace maker is put just below the right collarbone. It lasts for 2 years and impervious to body fluids and do not cause tissue reaction.

1.5.6. Valve Defects

Another heart disease is defective heart valves. These are of two types.

1) The valve either does or opens wide enough (stenosis). In stenosis large amount of work is to be done by heart to obstruct the narrow opening.

2) It does not close well enough (insufficiency).In insufficiency some of the pumped blood flows back and the amount of blood in circulation is reduced .Both types can be replaced by artificial valves.

1.5.7. Cardiovascular Diseases

Aneurysm

Some cardiovascular diseases involve the blood vessels. An aneurysm is a weakening of the wall of an artery which results increase in its diameter in turn increases the tension in the wall proportionately. If it is ruptured in brain, a type called Cerebrovascular accident (CVA).

A more common blood vessel problem is the formation of sclerotic plaques on the walls the artery which causes turbulence in blood flow increases the blood velocity at that point with a decrease in wall pressure due to Bernoulli’s theorem.

A Disease in Varicose Vein

Veins with defective valves which allow the blood to flow backward become enlarged or dilated to form the varicose veins. During walking or other exercise, the contraction of the muscle forces the venous blood toward the heart called venous pump. At various points along the veins there are one way flaps or valves that prevent the blood from going back. If these valves become defective blood run backward and pool up in the vein becomes “varicose”. The standard treatment for varicose veins is surgical removal of the offending vessels. There are sufficient parallel veins to carry the blood back to the heart.

Stiffness of RBC Membrane

In some cases, mainly in smoking, the membrane of RBC s becomes stiff. There may not be normal flow of blood in the vascular system. Blood may become viscous leading to Thrombosis.

1.6. Electrophysiology of Heart

The rhythmical action of the heart is considered by an electrical signal initiated by spontaneous stimulation of special muscle cells located in the upper right hand corner of the right atrium near the superior vena cava. This area is known as “sino atrial node”

(Fig 1.5).

Cardiac electro physiology is dedicated to the study of the electro chemical activity of the heart. Studies include electrical activation of individual cells as well as the system- level activation, which results in normal or abnormal heart rhythm. (J.Olansen et al 2000).

The complex system found by the Autonomous Nervous System (ANS) and the heart is modeled as if it was a modulation system, where the first generates a signal that modulates a sequence of pulses which excite the heart (Manuel Duarte Ortigueira et al 1959 ).

The sinus rhythm fluctuates around the mean heart rate, which is due to continuous alteration in the autonomous neural regulation i.e. sympathetic and parasympathetic balance. Periodic fluctuations found in heart rate originate from regulation related to respiration, blood pressure (baroreflex) and thermoregulation (Pauli Tikkanen 1999).

Cells in the SA node generate their electrical signal more frequently than cells else where in the heart. These impulses spread rapidly through inter nodal pathways to Atrioventricular node (AV node). At this node the signal is delayed so that all muscle cells of the atria contract virtually in unison. Now the impulse conducts through fibrous connective tissue between atria and ventricles known as “Atrio ventricular bundle “(AV bundle). AV bundle conducts the signal through left and right bundles of “Purkinje fibers” which conduct the cardiac signal to all parts of the ventricles.

1.5.Fig. Electrophysiology of the heart.

1.6.1. Sinoatrial Node

The sinoatrial node is a small, flattened ellipsoid strip of specialized muscle about 3 mm wide, 15 mm long and 1mm long located at the upper right hand corner of the right atrium immediately below and slightly lateral to the opening of the superior vena cava.

The Sinoatrial (SA node), the atrioventricular (AV node) and the Purkinje system can be regarded as potential pacemaker tissues in heart. As the fastest depolarization impulse spreads through the conduction system to other pacemakers before they spontaneously depolarize, the sinoatrial node usually defines heart rate (Pali Tikkanen 1999 12).

The sinus nodal fibers connect directly with the atrial muscle fibers, so that any action potential generates at the sinus node spreads immediately to the atrial muscle wall. For this reason Sinoatrial node is also known as “pace maker” of the heart. It generates the impulse at the rate of about 70/min and initiates the heart beat. However this rate may increase or decrease by the demand of blood supply to the body.

Three types of membrane ion channels play an important role in causing the voltage charges the action potential. They are 1) fast sodium channels 2) slow calcium-sodium channels 3) potassium channels. As the ions move in muscle cells in fractions of second creates action potential at the Sinoatrial node. This can be observed in spikes and plateau region in the graph plotted between time and membrane potential which is about -55 to -65 mV. This muscle much less negativity compared to ventricular action potential which is -85 to -90 mV is due to slow calcium- sodium channels.

The discharge rate of Sinoatrial node is faster than A-V node or Purkinje fibers. SA node generates impulse before either the A-V node or Purkinje fibers can reach their threshold for self excitation and this process continues on and on. Thus SA node controls the heart beat because its rhythmical discharge rate is greater than any other part of the heart. Therefore, the SA node is the normal "pace maker" of the heart.

1.6.2. Atrioventricular Node

The AV node is located in the posterior wall of the right atrium just behind the tricuspid valve. The cardiac impulse travels from the atria to ventricles relatively slow and this delay allows atria to empty the blood into ventricles before they start contracting.

The reason for delay of impulse is due to presence of connective tissue partition by a small bridge of muscle called atrio ventricular conduction system.

1.6.3. Atrioventricular Bundle (AV Bundle of His)

After making its way through the AV node an impulse passes along a group of muscle fibers called the A.V bundle or bundle of His. The special characteristic of the AV bundle is they prevent reentry of cardiac impulses from ventricle to atria but from atria to ventricle only.

1.6.4. The Purkinje Fibers

The Purkinje fibers lead from the A-V node through the A-V bundle into the ventricles. The initial part of Purkinje fibers is penetrated through bundle. They are very large fibers, even larger than the normal ventricular muscle fibers and transmit action potential at a velocity of 1.5 to 4.0 m/sec, which is about 6 times the usual ventricular muscle and 150 times that of in some of the AV nodal fibers. Purkinje fibers immediately transmit the cardiac impulse through the entire ventricular muscle.

The rapid transmission of action potential is due to high permeability of the gap junctions at the intercalated between the successive cardiac cells that make up the Purkinje fibers. As a result ions are transmitted easily from one cell to another increase velocity of impulse.

The Purkinje fibers divide into left and right bundle branches that lie under the endocardium on the two respective sides of the ventricular septum. Each branch spreads downward and divides into smaller branches covering ventricular chamber and back toward the base of the heart.

The ends of the Purkinje fibers penetrate into the muscle mass and finally become continuous with the cardiac muscle fibers as the ventricular walls are so thick and massive. The electrical impulse spreads from the SA node through the heart in less than one second.

1.7. Electrocardiogram

When the cardiac impulse passes through the heart: electrical current also spreads from the heart into the adjacent tissues surrounding the heart. A small portion of the current spreads all the way to the surface of the body. If electrodes are placed on the body skin on opposite sides of the heart: electrical potentials generated by the current can be recorded. The recording is known as "Electrocardiogram".

1.7.1. Historical Milestones of ECG

1887 : Augustus Desire Waller, recorded electric current preceding cardiac contraction.

1903 : Einthoven developed string galvanometer

1911 : Sir Thomas Lewis published his pioneering paper on ECG

1929 : Dock, use of cathode ray oscilloscope for ECG

1932 : Wolferth CC and Wood CC introduced chest leads

1942 : GoldbergerE, introduced unipolar limb leads (Dash 2002).

Nowadays, the HR-ECG is performed through the use of signal mean value estimation technique, based on multiple applications of average operations of the electrocardiographic signs (Manuel Duarte Ortigueira et al 1959).

Heart rate is obtained by analyzing electrocardiograms (ECG s), which are traces of the electrical activity of the heart measured by leads (Isla Gilmour 1995).

Depending on the electrodes involved in taking over the signal, more derivations are obtained and EKG signal is represented as a sequence of sample of variable length (Cosmin Cernazanu et al 1996).

Locating ECG waveform fiducial points (QRS complex,J point, on set and offset of T wave) is crucial step in automated ECG analysis for amplitude and interval measurements (Sahambi et al 1996).

Each beat of the heart can be observed as a series of deflections away from the baseline on the ECG. These deflections reflect the time evolution of electrical activity in the heart which initiates muscle contraction (Mcsharry et al 2003).

Fig 1.6. Electrocardiogram of the heart.

When the electric signal generated at Sino atrial node and passes through the heart and the same is spreads to adjacent tissues surrounding the heart. This electrical field passes through numerous other structures including the lungs, blood and skeletal muscle before reaching the body surface. These structures known as transmission factors differ in their electrical properties and perturb the cardiac electrical field as it passes through them. The potentials reaching the skin are then detected by the electrodes placed on specific locations and the electric potentials generated by the current can be identified, amplified, filtered and recorded in different electronic devices known as "Electrocardiogram"

(Fig. 1.6).

The electrocardiogram as used today is the product of a series of technological and physiological advances. Early demonstrations of the heart's electrical activity reported during the last half of the 19th century. The establishment of the clinical electrocardiogram (ECG) by the Dutch physician Willem Einthoven in 1903 marked the beginning of a new era in medical diagnostic techniques, including the entry of electronics into health care.

1.7.2. Characteristics of the Normal ECG

ECG signals include frequencies from 0.05 Hz to 200 Hz, but up to 100 Hz are adequate for clinical diagnostic purpose.

The normal electrocardiogram is composed of a P wave, a QRS complex, a T wave and a U wave (fig1.6)

P wave: - It is caused by electric potential generated when the atria depolarize before atrial contraction begins.

QRS complex: - It is due to potentials generated when the ventricles depolarize before their contraction.

T wave: - It is due to potentials generated when the ventricles recover from the state of depolarization.

U wave: - It fallows T-wave and is due to repolarization of the Purkinje fibers which is occasionally seen.

The heart is activated with each cardiac cycle in a very characteristic manner determined by the anatomy and physiology of working cardiac muscle and the specialized cardiac conduction systems.

P- Wave is generated by activation of the atria, the PR segment represents the duration of atrioventricular conduction (AV conduction), the QRS complex is produced by activation of both ventricles and ST-T wave reflects ventricular recovery.The voltages measured in ECG depend upon the locations of the electrodes applied to the surface of the body and how closely the electrodes are placed to the heart.

When ECG is recorded from standard combination i.e. two arms and one leg or one arm and two legs, the potential of the QRS complex is about 1 mv from the top of the R-wave to the bottom of the S-wave. The voltage of the P-wave is between 0.1 and 0.3 mv and that of T - wave between 0.2 and 0.3 mV.

1.7.3. Electric events in the heart

Location in the heart	Event	Time [ms]		ECG terminology	Conduction velocity [m/s]		Intrinsic frequency [1/min]
SA node atrium, Right Left AV node bundle of His bundle branches Purkinje fibers endocardium Septum Left ventricle epicardium Left ventricle Right ventricle epicardium Left ventricle Right ventricle endocardium Left ventricle	impulse generated depolarization *) depolarization arrival of impulse departure of impulse activated activated activated depolarization depolarization depolarization depolarization repolarization repolarization repolarization	0 5 85 50 125 130 145 150 175 190 225 250 400 600		P P P-Q interval QRS T	0.05 0.8-1.0 0.8-1.0 0.02-0.05 1.0-1.5 1.0-1.5 3.0-3.5 0.3 (axial) - 0.8 (transverse) 0.5		70-80 20-40

The relationship between the pumping action of the heart and the electrical potential on the skin reveals the propagation of an action potential in wall of the heart. Before stimulation of syncytial mass of cardiac muscle, all the exteriors of these cells had been positive and the interiors negative. After depolarization of syncytium negative charges leak to the outside of the depolarized muscle fiber making this surface area electronegative and the remaining part of the heart is still positive. The potential distribution for the entire heart when the ventricles are one-half depolarized is shown by the equipotential lines (Fig 1.7).

Fig 1.7. Equipotential lines around human heart

The form of potential lines can be represented as electric dipole. The equipotential lines at other times in the heart's cycle can also be represented by electric dipoles of different moments in the cycle would differ in size and orientation. The algebraic averages of all the lines of current flow occur with negativity toward the base of the heart and with positivity toward the apex.

The electrical potential that we measure on the body's surface is merely the instantaneous projection of electric dipole vector in a particular direction. As the vector changes with time so does the projected potential. Electric dipole vector along with the three electrocrdiographic body planes (Fig 1.8)

Fig 1.8 Electrocardiographicplanes. RS,LA,RLand LLindicate electrodelocations on the right and left arms and legs.

The surface electrodes placed on body shows the electrical connections recording electrocardiogram. These electrodes are called standard bipolar leads. The term "bipolar" means that the ECG is recorded from two electrodes located on different sides of the heart. Lead means the combination of two wires and their electrodes to make a complete circuit.

Fig 1.9 RA, LA, and LL represent the points of Einthoven triangle

Lead I - The measurement of the potential between right arm and left arm.

Lead II - The potential between right arm and left leg

Lead III- The potential between left arm and left leg.

According to Willem Einthoven, Dutch Physiologist these three leads are called standard limb leads. The potential between any two gives the relative amplitude and direction of the electric dipole vector

Einthoven's triangle

This is a diagnostic means of illustrating that the two arms and the left leg form apices of a triangle surrounding the heart. The two pieces at the upper part of the triangle shows the points at which the two arms connect electrically with the fluids around the heart and lower apex is the point at which the leg connects the fluids (Fig 1.9).

Einthoven's Law

The electrical potential at third is the mathematical sum of the potentials measured between any two bipolar limb leads.

The major electrical events that can be measured using their combination are

1) the atrial depolarization i.e. P-wave

2) the atrial repolarization normally not observed in wave form

3) the ventricular depolarization i.e. QRS complex

4) the ventricular repolarization i.e. T wave.

These descriptions of the waveforms of the normal ECG represent the patterns most often observed in normal adults. Values for many of the intervals may vary as a function of age, race, gender and body habits and within individuals as a function of autonomic tone and activity level.

1.8. Echocardiogram

Echocardiography is an early medical application of ultrasonography. An echocardiogram is a test in which ultra sound is used to examine the heart. A single dimension images known as M - mode echo that allows accurate measurement of heart chambers.

Using a transducer in the form of electrodes placed on the chest (Tran thoracic echocardiogram) gives a two dimensional echo displaying cross-sectional slice of the beating heart including the chambers, valves and the major blood vessels that exit from the right and left ventricles.

By applying Doppler examinations the ultra sound beams will evaluate the flow of blood i.e. direction and velocity. Echocardiography evaluates the size of the chambers including the dimension and the thickness of the wall. In patients with long standing hypertension, the test can determine the thickness and stiffness of left ventricle walls.

Pumping function of the heart can also be assessed by echocardiogram. This measure is known as an Ejection fraction or EF. A normal EF is around 55 to 65 %. Numbers below 45 % show some disease in pumping strength of the heart, while numbers below 30 to 35 % represent some major disease. It can also assess the pumping activity of each chamber of heart and also the movement of each wall can be visualized.

Echocardiography reveals the structural thickness and function i.e. movement of each heart valve. Along with Doppler it helps to identify abnormal leakage across heart valves and determine their severity. It can also detect the volume status of blood in systemic circulation and also useful in diagnosing of fluid in the pericardium.

1.9. Heart Sounds and Phonocardiogram

The sounds from a normal heart rate in the frequency range of 20 to 200 Hz .They are "lub dub lub dub". But only two are ordinarily audible through a stethoscope at optimum positions. "Lub" is associated with closure of AV valve at the beginning of systole and "dub" is associated with closer of semi lunar valves at the end of systole.

The human ear is not most sensitive in the heart frequency range, so with electronic amplification the less intense sounds can be detected and recorded graphically as a "Phonocardiogram". This means of registering heart sounds that may be inaudible to the human ear, helps to delineate the precise timing of the heart sounds relative to other events in the cardiac cell.

Heart sounds, as heard through a normal stethoscope are produced by a biological membrane in the heart when an event such as the opening or closing of a valve, vibration of the cardiac structure or acceleration or deceleration of blood occurs (Hall et al,2000).

The first heart sound is heard at the onset of ventricular systole and consists of a series of vibrations with low frequencies. It is due to the contraction of the ventricles first causes sudden backflow of blood against the AV valves (tricuspid and mitral valves), causing them to close. The low frequencies are due to vibrations of the adjacent blood, walls of the heart and major vessels around the heart. The vibrations travel through the adjacent tissues to the chest wall, where they can be heard as sound by stethoscope.

The intensity of first sound is a function of the force of ventricular contraction and of the distance between the valve leaflets are farthest apart, as occur when the interval between atrial and ventricular systoles.

The second heart sound occurs from the sudden closure of the semi lunar valves. It is composed of higher pitch with shorter duration of lower intensity and has a more snapping quality than the first heart sound. When semi-lunar valves close, they bulge backward toward the ventricles, which initiates oscillations of the columns of blood and the tensed vessel walls by the stretch and recoil of the closed valve. Conditions that bring about a more rapid closure of the semi lunar valves such that pulmonary or systemic hypertension increases the intensity of second heart sound.

Fig.1.10. A comparison of ECG and PCG

Phonocardiogram takes simultaneously with ECG as shown in fig, the first sound starts just beyond the peak of R-wave which is composed of irregular waves and is of greater intensity and duration. The second sound which appears at the end of the T-wave.

A third and fourth sound do not appear on this record.

The third heart sound is a week and occurs occasionally, which consists of low intensity, low frequency vibrations heard best in the region of the apex. It occurs at the beginning of the middle third of diastole and is believed to the result of vibrations of the ventricular walls when the ventricles are not filled sufficiently to create even the small amount of elastic tension required for reverberation. The frequency is so low that can not be heard normally but can be recorded using Phonocardiogram.

A fourth is an atrial sound consisting of a few low frequency oscillations is not heard in general but can be recorded using Phonocardiogram. It is caused by oscillation of blood and cardiac chambers created by atrial contraction.

1.9.1. Phonocardiogram

A microphone specially designed to detect low frequency sound is placed on the chest. The heart sounds can be amplified and recorded by a high speed recording apparatus known as Phonocardiogram.

Abnormal heart sound due to valvular lesions is known as "heart murmurs". The Phonocardiogram show how the intensity of murmur varies during different portions of systole and diastole.

1.10 Photoplethysmography (PPG)

Photoplethysmography (PPG) is a simple and low cost optical techniques that can be used to detect blood volume changes in the microvascular bed of tissue. It is often used non- invasively to make measurements at the skin surface. The PPG waveform comprises a pulsatile(AC) physiological waveform attributed to cardiac synchronous changes in the blood volume with each heartbeat, and is superimposed on a slowly varying (DC) baseline with various lower frequency components attributed to respiration sympathetic nervous system activity and thermoregulation.

Photoplethysmography is based on the determination of the optical properties of a selected skin area. For this purpose IR light is emitted into the skin. Light is absorbed, depending on the blood volume of the skin. Consequently, the backscattered light corresponds with the variation of the blood volume. Blood volume changes can then be determined by measuring the reflected light and using the optical properties of tissue and blood.

Fig. 1.11. photoplethysmography and its graph

There are two different types PPG probes that can be used.

1. Reflection probes: This type probe can also be used for the venous test. The light emitting and sensitive parts are located side by side in one probe. The photo sensors detect the light, which is backscattered from the tissue of the skin. Due to the body's anatomy, the PPG sensors can only detect the pulse waves in areas that contain many arteriovenous anastomoses such as fingers, toes, earlobes or some regions of face.

2. Transmission probes: In these probes the photo sensors are located on the opposite side as the light emitting parts. The tissue is located between them. This limits the field of application to locations where the light can penetrate all the way through the tissue (fingers, toes, earlobes). In contrast to the reflection probe, the main sources of pulsation also contain the large vessels making these sensors especially useful for peripheral blood pressure measurements.

The arterial photoplethysmography measures and evaluates the shape and size of the pulse waves. The easy application in fingers and toes make this method especially useful in:

• Diagnosing arterial disease in fingers and toes by just watching the curve.
• Diagnosing the functional disturbances of blood flow (Raynoulds sunchrome, death finger, fibration syndrome).
• Diagnosing chronic venous diseases such as varicose veins and other disorders that cause by swelling and leg ulcers.
• Measuring peripheral blood pressure even on digits (using transmission probes).

1.11. Survey of Literature on Electro Physiology of Heart

Manuel Duarte Ortigueira et al (1959) described that a new algorithm can be adopted to study the heart frequency and interpretation of ECG by applying archetypal analysis (prototype analysis). This study helped to clean the ECG waves from noise and isolating them. The isolated waves are normalized and aligned depending upon the average of original beats.

Joseph D. Touch (1986) presented a statistical method for relative peak detection in ECG signal by simple threshold and slope change detection algorithms.

Isla Gilmour (1995) described that a neural sensor called the baroreceptor was used to obtain the coupled fluctuations of blood pressure and heart rate time series by involving Fourier techniques.

Gianfranco Parati et al (1995) criticized that a concise and critical description of the spectral methods most commonly used (fast Fourier transform versus autoregressive modeling , time varying versus broad band spectral analysis) and an evaluation of their advantage and disadvantages. It also provides insight into the problems that still affect the physiological and clinical interpretation of data provided by spectral analysis of blood pressure and heart rate variability (HRV). In particular the assessment of blood pressure and heart rate spectra aimed at providing indices of autonomic cardiovascular modulation was discussed. Evidence was given that multi variate models which allow evaluation of the interaction between changes in blood pressure, heart rate and other biological signals in the time or frequency domains offer a more comprehensive approach to the assessment of cardiovascular regulation than that represented by the separate analysis of fluctuations in blood pressure or heart rate only.

The European society of cardiology and the North American Society of pacing and Electrophysiology (1996) issued guidelines to measure heart rate variability.

Cosmin Cernazanu et al (1996) described that 15 heart diseases can be diagnosed by using the EKG signal with the help of neural networks. They described how the EKG was initially filtered, how each of the three constituents of the signal. (The P - wave, the QRS complex and the T- wave) had been recognized and interpreted by a neural network, the three interpretation of the constituents and other data had been analyzed by using a neural which established a diagnosis.

Sahambi, et al (1996) proposed an algorithm for ST segment analysis was developed using the multi resolution wavelet approach. The algorithm had been implemented on TMS320C5 based add-on DSP card to PC to provide the on-line analysis and display of ST-segment data. The performance of the system was evaluated using the standard ECG waveforms with different morphologies and heart rates in order to take into account the variability of the data encountered in the clinical environment.

Garrett Stanley et al (1997) presented that age effects on interrelation ships between lung volume and heart rate during standing. Age and position affects and age position interactions were determined by analysis of variance for repeated measures.The spectral estimates were generated using fast Fourier analysis techniques that employ a hamming smoothing window.

Time Makikallio (1998) presented that to assess the clinical applicability of new dynamical analysis methods derived from nonlinear dynamics of heart rate behavior.

This study covered four different patient populations. Electrocardiographic recordings of subjects were taken. The data were sampled digitally and transferred to microcomputer for the analysis of heart rate variability. The Fourier transform method was used to estimate the power spectrum densities of heart rate variability.

Clayton and Murray (1998) compared the time frequency analysis of the ECG during human ventricular fibrillation. This paper focused in using linear and non-linear signal processing techniques to characterize recordings of VF. Time Frequency Distribution (TFD) of the first tens these recordings were estimated with the short time Fourier transform, Wigner-ville, smoothed Wigner -ville and Choi -williams algorithms. Used in tandem with the predictable short time Fourier transform, the smoothed Wigner TFD was a valuable tool for characteriging the TFD of human VF.

Havlin et al (1999) studied in his paper that statistical physics can be applied to heart beat diagnosis. Several studies had revealed that statistical physics concepts that can be used as diagnostic tools for heart failure. They described the sealing exponent characterizing the long range correlations in heart beat time series as well as the multifractal features discovered in heart beat rhythm. It is found that features, the long range correlations and the multifractility are weaker in cases of heart failure.

Piotr Rozentryt et al (1999) presented that amplitude of ECG potentials varies on a beat- to- beat basis. This variability could be seen in different parts of ECG cycles and was usually periodic in nature. In their study they presented a new method allowing analysis which investigates the distribution of variability power in time and frequency domains (spectro temporal maps). A new feature of the method was its ability to attenuate errors in amplitude variability measurements coming from RT interval alterations. They also presented examples of spectro-temporal maps obtained in healthy subjects, surgically denervated patients after heart transplantation and patients with coronary artery disease.

Pauli Tikkanen (1999) reported in his thesis the quantitation of the variability in cardiovascular signals provides information about the autonomic neural regulation of the heart and the circulatory system. An ambulatory measurement setting is in important and demanding condition for the recording and analysis of these signals. In addition to heart rate variability (HRV) measurement using RR intervals, the dynamics of ventricular repolarization duration (VRD) is considered using the invasively obtained action potential duration (APD) and different estimate for QT intervals taken from a surface electrocardiogram (ECG). Further the estimation of the power spectrum is presented on the approach using an autoregressive (AR). The power spectrum analysis is examined by means of wavelet transforms, which are then applied to estimate the non-stationary RR interval variability.

John M.Karemaker (1999) presented that when Fourier analysis was applied to analysis of BP Variability(BPV) and HR Variability(HRV), two frequency peaks stood out ; one around the respiratory frequency and one around 0.1 Hz. The respiration -coupled blood pressure oscillations were partly explained by mechanical effects of respiration and possibly by the vagally induced heart period oscillations coupled to respiration known as Respiratory Sinus Arrhythmia(RSA)The Journal of Physiology

Clayton et al (1999) proposed to compare Pseudo-ECGs produced by different configuration of re-entry in a computational model. They initiated single, double and multiple re-entrant waves in a cuboid with Fitz- Hugh Nagumo excitability and estimated one component of the pseudo-ECG and applied linear time frequency and non-linear dimensional analysis. The pseudo -ECG produced by a single re-entrant wave was periodic, where as that produced by a double re-entrant wave was quasiperiodic with slow changes in both frequency content and amplitude. The dimensions of these time series were around 1 and 3 respectively. For pseudo ECG it was more complex and its dimension was around 4. Thus different configurations of re-entrant wave were associated with qualitatively and quantitatively different pseudo-ECG time series.

Szili-Torok, et al (1999) presented that the spectral assessment of HRV and blood pressure variability can be studied with continuous ECG and non-invasive BP recordings on subjects during head-up tilt testing were subjected to analysis. The total spectral power and the power over the low and the high frequency spectral bands were recalculated in an overlapping series with constant time shifting of the initial data - point. Window fast Fourier transformation was applied for assessment of dynamic HR and BP spectral changes during upright tilt testing.

Narayana Dutt and Krishnan (2000) discussed that high performance computing has made a great impact in recent times in achieving practical solutions to problems in health care. Computational efficacy of various techniques had been discussed and examples from critically ill patients of ICCU were taken using real world HRV data were presented. In addition to giving applications to patient care in ICCU, other methods were to also discuss in view of their potential application to critical care medicine.

Malvin C. Teich et al (2000) studied that the statistical behavior of the sequence of heart beats can be studied by replacing the complex waveform of an individual heart beat recorded in the ECG. They developed a mathematical point process that emulates the human heart beat time series for both normal subjects and heart -failure patients.

Cornelius keyl, et al (2000) discussed that Respiratory Sinus Arrhythmia (RSA) originates mainly from a central coupling between respiration and heart rate or from baroreflex mechanisms. They applied a sinusoidal stimulus to the carotid baroreceptors and generated heart rate fluctuations of the same magnitude as RSA with a frequency similar to, but different from, the breathing frequency. The data were analyzed using discrete Fourier transform and transfer function analysis. Respiratory fluctuations in systolic blood pressure preceded RSA with a time lag equal to that between baroreceptor stimulation and oscillations in RR interval.

Olansen et al (2000) described that the development of a variety of classical biomedical experiments. These are not only reinforcing basic knowledge but also train students in the application of these theories to laboratory research.

Hall et al (2000) discussed that heart sounds can be utilized more efficiently by medical doctors when they are displayed. A system where by a digital stethoscope interface directly to a PC will be described along with signal processing algorithms adopted. The sensor is based on a noise cancellation microphone. They developed a solution using "wavelet denoising". Thus coding of the waveform into the wavelet domain is achieved with relatively few wavelet coefficients in contrast to the many Fourier components that would result from conventional decomposition.

Ranveig Nygaard et al (2001) presented that a time domain algorithm based on the coding of line segments which are used to approximate the signal. These segments are fit in a way that was optimal in the rate of distortion sense. The approach was applicable to any signal but they focused on compression of ECG signals. Evaluation was based on both on percentage root-mean square difference (PRD), performance measure and visual inspection of the reconstructed signals. IEEE Transactions on Biomedical Engineering Vol 48 No 1

Richard P. Sloan et al (2001) discussed that considerable evidence implicates hostility in the development of coronary artery disease; the pathogenic mechanisms remain poorly understood. They developed a psycho physiological model that holds that altered autonomic nervous system function links psychological trails with CAD outcomes. With ambulatory electrocardiographic recording they demonstrated in a predominantly male sample that hostility was inversely associated with HF power, but only during working hours. These findings were consistent with the hypothesis that hostile individual experience multiple stressful interpersonal transactions each day, resulting in overall lower HF power during the day but not at night.

Dash (2002) discussed that good knowledge on the basics with attention to technical details goes to long way. Application of advanced technology in ECG monitoring gives maximum information and should be utilized to its fullest extent.

Seria Mecanica (2002) presented that possibilities of higher order spectral methods in biological signal processing in a concise form were introduced the second order spectrum, the third order spectrum (bisprectrum) and the coherence function of a signal. These transforms were applied to ECG & Phonocardiographic signals.

Patrice E.Mesharry et al (2003) developed a dynamical model based on three coupled ordinary differential equations was introduced which was capable of generating realistic synthetic electrocardiogram (ECG) signals. The operator could specify the mean and standard deviation of the heart rate, the morphology of the PQRST cycle and the power spectrum of the RR-tachogram.

Kalda Sakki, et al (2003) described elaborate efficient and adequate tools for the analysis of human heart rate fluctuations, as it is a complex and non-stationary wave. They classified the measures of heart rate variability as

1. Linear methods- applied Fourier analysis based on standard statistical measures.

2. Non - linear methods

a) Scale -invariant methods

b) Scale -dependent methods.

Naidu and Reddy (2003) developed autoregressive moving average (ARMA) method to study frequency domain representation of a short term heart rate time series (HRTS) signal was used for evaluating the cardiovascular control system. The spectral parameters used were ,percentage power in low frequency band(%PLF), percentage power in high frequency band (%PHF), power ratio of low frequency to high frequency(PRLH) , peak power ratio of low frequency to high frequency (PPRLH) and total power (TP)Results obtained from ARMA - based analysis of heart - rate time series signals were capable of complementing the clinical examination results.

Itrarce A Dachi et al (2003) presented that the ventricular phase angle, a parametric method applied to Fourier phase analysis (FPA) in radionuclide ventriculography , allows the quantitative analysis of ventricular contractile synchrony ,FPA reproducibility using gated blood pool SPECT (GBPS) could be improved over that in planar radionuclide angiography(PRNA).

Maarvili, et al (2003) presented an algorithm to detect the first heart sound(S1) and second sound (S2). The algorithm utilizes instantaneous energy of Electrocardiogram (ECG) to estimate the presence of S1 and S2.

Patrick E. Mcshany and Gari D. Clifford (2004) developed software for generating electrocardiogram signals, ECGSYN. A dynamical model that faithfully reproduces the main features of the human electrocardiogram (ECG), including heart rate variability, RR intervals and QT intervals was presented. Details of the underlying algorithm and open -source software implementation in Mat Lab C and Java were described.

Nathan A Wedge, et al (2004) studied the characteristics of excitable cell mathematical models, with the goal of developing new insights and techniques in simulating the electrical behaviour of the human heart .They presented an examination of the Fitz Hugh- Nagumo model and its response to stimulus and in order to move toward the goal of full cardiac simulations. They adopted a method of optimizing single- cell calculations through local interpolation techniques. In addition to it they introduced a separate method of optimizing multi - cell simulations by tracking cellular activations

Lambros V. Skalars et al (2004) presented a new approach in modeling the electrical activity of the human heart. A recurrent artificial neural network was used in order to exhibit a subset of the dynamics of the electrical behaviour of the human heart. The proposed model could also used, when integrated as a diagnostic tool of the human heart system. This diagnostic system aimed to accomplish two major roles .Firstly, become a useful tool for health care practitioners in the area of diagnosis. Secondly it used as a simulator for biological systems used in education and research related to human physiology.

Petra Barthel, et al (2004) studied that heart rate turbulence (HRT) was a measure of the autonomic response to perturbations of arterial blood pressure after single ventricular premature complex. HRT was a simple and non-invasive method to assess baroreflex function. In post infarction patients HRT was a potent risk stratification tool and provides informa of left ventricular function.

Esther Pueyo, et al (2004) studied that the QT interval response to RR interval changes was assessed in 24 - hour Holter recordings by considering weighted averages of a history of past RR intervals to characterize the influence of heart rate on each QT measurement. Two main results were found in this study, first the process of QT adaptation to rate changes was highly individual and second RR interval variations some previous minutes to completely characterize the QT response.

Luigi De Ambroggi and Alexander D. Corlan (2004) studied the complexity of T - Wave using multiple thoracic leads or 12-lead ECG. According to them Body surface potential maps (BSPM) ware advantageous over the conventional 12 leads. This could analyze repolarization potentials. They were instantaneous potential distribution QRS-T integral maps, eigenvector analysis, principal component analysis and auto - correlation analysis.

Walid El-Atabamy et al (2004) discussed that cardiac arrhythmias disrupt the normal synchronized contraction sequence of the heart and reduce the pumping efficiency. The detection and classification of such arrhythmias was essential. In this paper four types of ventricular arrhythmias (PVC, VB, VT and VF) were considered. A no. of features was extracted from ECG signal using a nonlinear dynamical signal analysis technique, recurrence dynamical analysis (RQA). Then three statistical classifiers were used in the classification. Results confirmed the robustness of the new techniques and demonstrate its value as a new diagnostic tool.

Tom Froese (2004) presented classification results of ECG signals with pathological conditions after they had been translated into the wavelet domain. Both the traditional Linear Discriminant Analysis method and the connectionist Multi- Layer Perception classifier were used on the problem and their results compared and contrasted. It was shown that the much simpler signal representation of a few wavelet coefficients obtained through the discrete wavelet transform eases the classification of time-variant signals considerably.

Morteja Moazami, et al (2004) introduced ECG compression algorithm based on two dimensional multi wavelet transform. Multi wavelets offer the possibility of superior performance for image processing applications. They studied SPIHT algorithm to achieve the clinical diagnosis.

Mohammed Pooyam, et al (2004) presented wavelet compression of ECG signals based on Set partitioning in hierarchical trees (SPIHT) coding algorithm. SPIHT is applied to the one dimensional analysis.

Lambros V. skarlas, et al [2004] presented a neural network to exhibit a subset of the dynamics of the electrical behavior of the human heart.

Zoltan German sallo (2005) described that each heart beat is a complex of distinct cardio logical events represented by distinct features in the ECG waveform. The proposed tasks concerning the three topics (preprocessing, parameter extraction and application of soft computing methods) were accomplished with relatively good results with the multi scale feature of wave transforms, various morphologies were excited better at different scales. A comprehensive comparative study to choose the best wavelet function for ECG signal processing purposes, using self synthesized test signals and decomposition - reconstruction error as a criterion.

Geng Hong et al (2005) studied that the measurement of Heart Rate Variability (HRV), provides a non- invasive measurement of the autonomic nervous system (ANS) activity. HRV can be measured with the variation of RR intervals exhibited in a sequence of ECG sample. In this paper they analyzed and evaluated the measurement results based on three minute and five minute HRVs. Four major measurements were ,first the standard deviation of normal -beat to normal-beat intervals(SDNN) second square root of the mean squared difference of successive difference normal-beat to normal-beat intervals(RMSSD) ,third the proportion of interval difference of successive normal-beat to normal-beat intervals greater than 50ms (Pnn50), fourth the ratio of low frequency energy to high frequency energy (LF/HF) based on Fourier analysis method . Results had shown that the HRV presented by both SDNN and LF/HF using the 3-minute measuring data diffrs significantly from that using 5-minute measuring data.

Alireza Akhbardeh, et al (2005) discussed that among different methods used for analyzing heart conditions and monitoring their body's signals. They proposed a new method Ballistocardiography (BCG) to analyze the same without attaching electrodes on the body during recording. They used shift Invariant Daubochies wavelet transform to extract essential BCG features and Artificial Neural Networks to classify them. They were proved reliable and high performance.

Gari D.clifford (2006) presented that changes in the ECG were quasi periodic ,the frequency can be quantified in both statistical terms. In essence, all these statistics quantify the power or degree to which no oscillation was present in a particular frequency band often expressed as a ratio to power in another band. Even for scale frequency approaches the process of features extraction tends to have a bias for a particular scale. ECG statistics were evaluated directly on the ECG signal.

Michal Huptych, et al (2006) presented an overview of a software tool for preprocessing, analysis and visualization of ECG signal. Their work was to automate the task of preprocessing, analysis and visualization, signal frequency, decomposition and map creation by multi - channel measurement from patient body surface (Body surface potential mapping). Signal frequency decomposition was performed by continuous wavelet transform. The software tool had been programmed in Java and tested on the data acquired from the CARDIAC 1122 system which measures signals from 80 unipolar electrodes evenly placed on the body surface.

Ming Jiang (2006) described that the areas of remote ECG feature extraction utilizing wavelet transformation concepts and sensor network system at low cost and Low-power wearable platforms provide continuous ECG monitoring which by measuring potentials between various points on the body using a galvanometer. The system was enabled with integrated RF communication capability that relay the signals wirelessly to a work station monitor .The work station was equipped with ECG signal processing software that performs ECG characteristic extraction via wavelet transformation.

Mirko Degli Esposh et al (2006) discussed a similarity distance function between symbolic strings recently introduced. Application to phylogenetic tree construction and HRV analysis were considered.

Chouhan and Mehta (2006) presented algorithm employs a modified slope of ECG signal as the feature for detection of QRS. A sequence of transformation of the filtered and base line drift corrected ECG signal is used for extraction of a new modified slope feature.

Anirudha Joshi (2006) proposed that a novel hybrid Holder-SVM detection algorithm for arrhythmia classification. The Holder exponents were computed efficiently using the Wavelet Transform Modulus Maxima (WTMM) method.

Debbal and Bereksi-Reguing (2006) studied that the continuous wavelet transform provides enough features of the PCG signals that will help clinics to diagnosis. It was shown that the frequency content of such a signal can be determined by the FFT without difficulties. In their study it was discussed that second heart sound 32 consists of two major components (A2 and P2) with a time delay between them is very important for medical diagnosis.

Yanyan Hao, et al (2007) proposed compression of ECG as a signal with finite rate of innovation (FRI). By modeling the ECG signal as the sum of hand limited and non-uniform linear spline which contains finite rate innovation (FRI). The simulation results had shown the performance of the compression of ECG as a signal with FRI was quite satisfactory in presenting the diagnostic information as compared to the classical sampling scheme which uses the sine interpolation

Elena Visotska, et al (2007) presented successful application biorthogonal wavelet transform had allowed statistically characterize not only ECG signal and wavelet components but also to receive with authentic accuracy distinctive characteristics of two compared ECG signals. Decisions of problems during forecasting and early diagnostics of heart attack, also in time revealing of fatal infringements of heart rhythm, the prevention sudden coronary death were considered in this work.

Sinisa S.Ilic (2007) proposed that Continuous Wavelet Transform (CWT) diagram of healthy patients and patients with Left Bundle Branch Block (LBBB) were easy to distinguish. The concentration of CWT coefficients with higher amplitude was at lower frequencies for patients with LBBB to healthy patients. The sequence of segments in the ECG signal can be identified in CWT diagram too. Correlation between specific ECG waveforms and carefully chosen wavelets could be at higher and it might result in better recognition of characteristic segments in ECG signal.

Elif Derya Ubeyl (2007) studied the automated diagnostic systems employing diverse and composite features was analyzed and their accuracies were determined. Combining multiple classifiers with diverse features is viewed as a general problem in various applications areas of pattern recognition.

Xanthis et al (2007) developed an improved solution of the non- linear and ill-posed inverse problem of ECG was presented. For this purpose a three dimensional volume conductor model of the human body is constructed based on a classical anatomic atlas.

Swaroop S singh et al (2007) studied on retrospective ECG recordings of patients during cardiac arrest have shown significant changes in heart rate variability indices increases prior to the onset of cardiac arythmia. The Early detection of these changes in HRV indices is for a successful medical intervention to decrease the rate of cardiac arrest.

Debbal and Bereksi - Reguing (2007) had presented the synthesis study of the Fast Fourier transform (FFT) in analyzing the phonocardiogram signal (PCG). It was studied that the spectral analysis van provide enough features of the PCG signals that will help clinicians to obtain qualitative and quantitative measurements of PCG signal characteristics and consequently aid to diagnosis.

Stridh et al (2007) developed a new method for ECG based characterization of atrial fibrillation (AF) which explores the morphology of the f- waves. Fallowing QRST cancellation, the method divides the atrial signal into short blocks and performs a model based analysis of each block. The blocks are then clustered into different waveform patterns.