This document discusses characterizing left ventricular hypertrophy (LVH) using fractional calculus techniques applied to electrocardiogram (ECG) graphs. It introduces LVH and defines fractional derivatives and phase transition. Tables compare measurements from normal and abnormal (LVH) ECG samples, showing increased length of waves and higher phase transition values at non-differentiable points in LVH cases. The study aims to distinguish LVH ECGs from normal using these fractional calculus-based measurements.
The document provides an overview of interpreting electrocardiograms (ECGs). It discusses the coronary circulation and electrical conduction system of the heart. It then covers the key elements of an ECG including the waveform and intervals in a normal reading. The document outlines how to interpret an ECG to identify lethal cardiac diseases by examining features such as the rate, rhythm, P waves, PR interval, and QRS complex. It provides guidance on evaluating the ECG for conditions like myocardial infarction by looking at changes in the ST segment across different electrode positions.
The document provides an overview of electrocardiograms (ECGs), including:
1) How ECGs work by measuring the electrical activity of the heart using electrodes placed on the body.
2) Details on Willem Einthoven who pioneered ECG research in the late 19th/early 20th century.
3) Explanation of normal ECG wave patterns and what different parts of the readout represent.
This document provides instruction on systematically analyzing a 12-lead electrocardiogram (ECG). It outlines a 6-step approach to analyze the ECG, covering the last 3 steps in this module:
1. Calculate the heart rate
2. Determine the rhythm
3. Determine the QRS axis
4. Calculate the PR, QRS, and QT intervals
5. Assess for evidence of right or left atrial and ventricular hypertrophy
6. Look for evidence of myocardial infarction by examining for abnormal Q waves, ST segment elevation or depression, and abnormal T waves
Criteria are provided to diagnose abnormalities in each of the last 3 steps.
An EKG records the electrical activity of the heart over time. It shows waveforms labeled P, QRS, and T that represent different events in the heart's electrical cycle and natural conduction pathways. Abnormalities in these waveforms can indicate disorders like arrhythmias, injury, or heart attacks. In this experiment, students will record their own EKG, identify the normal waveforms and intervals, calculate their heart rate, and observe how the tracing changes when electrode positions are altered to simulate a myocardial infarction.
The document provides information about electrocardiography (ECG) including its history, how an ECG machine works, how to perform an ECG, ECG waveform interpretation, and common cardiac rhythms and abnormalities. It discusses key aspects of an ECG such as rate, rhythm, cardiac axis, P waves, PR interval, and common rhythms including normal sinus rhythm, atrial fibrillation, ventricular tachycardia, and more.
An electrocardiogram (EKG or ECG) records the electrical activity of the heart over time. The main components of a heartbeat are labeled P, Q, R, S, and T waves. The P wave represents electrical activity spreading through the atria, while the QRS complex represents ventricular activation. The T wave occurs as the ventricles recover. By examining intervals between these waves, as well as their presence, shape, and consistency, doctors can detect disorders like abnormal heart rhythms or damage to heart muscle tissue. In this experiment, students will record their own EKG, identify the wave components, and calculate their heart rate. They will also compare EKGs recorded from different electrode placements on the arms
ECG analysis part (1) \ Mohammad Al-me`ani. , MSN, RN. almaani
The document discusses ECG analysis and provides details about:
1. The ECG records the electrical activity of the heart through electrodes placed on the skin. A 12-lead ECG provides views from 12 reference points.
2. The ECG traces the heart's electrical impulses on graph paper. It displays depolarization and repolarization processes and is used to diagnose various cardiac conditions.
3. The heart's conductive system includes the sinoatrial node, atrioventricular node, bundle of His, left and right bundle branches, and Purkinje fibers which coordinate heart rhythm and contractions.
To summarize the document:
1. The document outlines the steps for systematically analyzing a 12-lead ECG: rate, rhythm, axis, intervals, hypertrophy, and evidence of infarction.
2. It describes how to calculate and interpret the PR, QRS, and QT intervals and defines normal values.
3. Criteria are provided to assess for right and left atrial enlargement, right and left ventricular hypertrophy on the ECG.
4. The document instructs the reader to look for abnormal Q waves, ST elevation or depression, and T wave changes when analyzing the ECG for evidence of a myocardial infarction.
The document provides an overview of interpreting electrocardiograms (ECGs). It discusses the coronary circulation and electrical conduction system of the heart. It then covers the key elements of an ECG including the waveform and intervals in a normal reading. The document outlines how to interpret an ECG to identify lethal cardiac diseases by examining features such as the rate, rhythm, P waves, PR interval, and QRS complex. It provides guidance on evaluating the ECG for conditions like myocardial infarction by looking at changes in the ST segment across different electrode positions.
The document provides an overview of electrocardiograms (ECGs), including:
1) How ECGs work by measuring the electrical activity of the heart using electrodes placed on the body.
2) Details on Willem Einthoven who pioneered ECG research in the late 19th/early 20th century.
3) Explanation of normal ECG wave patterns and what different parts of the readout represent.
This document provides instruction on systematically analyzing a 12-lead electrocardiogram (ECG). It outlines a 6-step approach to analyze the ECG, covering the last 3 steps in this module:
1. Calculate the heart rate
2. Determine the rhythm
3. Determine the QRS axis
4. Calculate the PR, QRS, and QT intervals
5. Assess for evidence of right or left atrial and ventricular hypertrophy
6. Look for evidence of myocardial infarction by examining for abnormal Q waves, ST segment elevation or depression, and abnormal T waves
Criteria are provided to diagnose abnormalities in each of the last 3 steps.
An EKG records the electrical activity of the heart over time. It shows waveforms labeled P, QRS, and T that represent different events in the heart's electrical cycle and natural conduction pathways. Abnormalities in these waveforms can indicate disorders like arrhythmias, injury, or heart attacks. In this experiment, students will record their own EKG, identify the normal waveforms and intervals, calculate their heart rate, and observe how the tracing changes when electrode positions are altered to simulate a myocardial infarction.
The document provides information about electrocardiography (ECG) including its history, how an ECG machine works, how to perform an ECG, ECG waveform interpretation, and common cardiac rhythms and abnormalities. It discusses key aspects of an ECG such as rate, rhythm, cardiac axis, P waves, PR interval, and common rhythms including normal sinus rhythm, atrial fibrillation, ventricular tachycardia, and more.
An electrocardiogram (EKG or ECG) records the electrical activity of the heart over time. The main components of a heartbeat are labeled P, Q, R, S, and T waves. The P wave represents electrical activity spreading through the atria, while the QRS complex represents ventricular activation. The T wave occurs as the ventricles recover. By examining intervals between these waves, as well as their presence, shape, and consistency, doctors can detect disorders like abnormal heart rhythms or damage to heart muscle tissue. In this experiment, students will record their own EKG, identify the wave components, and calculate their heart rate. They will also compare EKGs recorded from different electrode placements on the arms
ECG analysis part (1) \ Mohammad Al-me`ani. , MSN, RN. almaani
The document discusses ECG analysis and provides details about:
1. The ECG records the electrical activity of the heart through electrodes placed on the skin. A 12-lead ECG provides views from 12 reference points.
2. The ECG traces the heart's electrical impulses on graph paper. It displays depolarization and repolarization processes and is used to diagnose various cardiac conditions.
3. The heart's conductive system includes the sinoatrial node, atrioventricular node, bundle of His, left and right bundle branches, and Purkinje fibers which coordinate heart rhythm and contractions.
To summarize the document:
1. The document outlines the steps for systematically analyzing a 12-lead ECG: rate, rhythm, axis, intervals, hypertrophy, and evidence of infarction.
2. It describes how to calculate and interpret the PR, QRS, and QT intervals and defines normal values.
3. Criteria are provided to assess for right and left atrial enlargement, right and left ventricular hypertrophy on the ECG.
4. The document instructs the reader to look for abnormal Q waves, ST elevation or depression, and T wave changes when analyzing the ECG for evidence of a myocardial infarction.
A M ODIFIED M ETHOD F OR P REDICTIVITY OF H EART R ATE V ARIABILITYcsandit
Heart Rate Variability (HRV) plays an important rol
e for reporting several cardiological and
non-cardiological diseases. Also, the HRV has a pro
gnostic value and is therefore quite
important in modelling the cardiac risk. The nature
of the HRV is chaotic, stochastic and it
remains highly controversial. Because the HRV has u
tmost importance, it needs a sensitive tool
to analyze the variability. In previous work, Rosen
stein and Wolf had used the Lyapunov
exponent as a quantitative measure for HRV detectio
n sensitivity. However, the two methods
diverge in determining the HRV sensitivity. This pa
per introduces a modification to both the
Rosenstein and Wolf methods to overcome their drawb
acks. The introduced Mazhar-Eslam
algorithm increases the sensitivity to HRV detectio
n with better accuracy.
The document discusses ECG signal analysis and abnormality detection using artificial neural networks. It defines normal and abnormal ECG signals, describing abnormalities like bradycardia and tachycardia. Two algorithms are described for detecting abnormalities: one analyzes heart rate and the other detects general heart diseases. An ANN system is used for ECG analysis and classification, taking spectral entropy, Poincare plot geometry, and largest Lyapunov exponent as inputs to classify eight cardiac conditions.
An electrocardiogram (EKG or ECG) records the electrical activity of the heart over time. It shows different wave components including the P wave, QRS complex, and T wave that represent the spread of electrical impulses through the heart's chambers and their contraction and relaxation. By analyzing the timing and appearance of these waves, doctors can detect abnormalities that may indicate heart conditions. In this experiment, students will use an EKG sensor to record their own heart activity, identify the wave components, and calculate their heart rate. They will also compare recordings from standard and alternate lead placements.
Case-1: ECG with Normal axis ; Case-2: ECG with left axis deviation
Case-3: ECG with extreme right axis deviation
Case-4: ECG with right axis deviation
Clinical significance of cardiac axis
What is Electrical Axis? Types of electrical axis
What are the Methods of ECG Axis Interpretation? How ECG axis can be determined?
How Ventricular (QRS) Axis is determined in Bundle Branch Blocks ?
What is Undetermined axis/ Indeterminate axis?
What are the causes of abnormal heart axis?
What are the causes of Right Axis Deviation(RAD)?
What are the causes of Left Axis Deviation?
What are the causes of Extreme Axis Deviation (indeterminate axis/ northwest axis)?
An electrocardiogram (ECG or EKG) records the electrical activity of the heart over time through electrodes placed on the skin. It shows five main components - P wave, QRS complex, and T wave - that represent the spread of electrical impulses through the heart during each heartbeat. Doctors can analyze features of the EKG like interval durations and waveform shapes to detect abnormalities and disorders of the heart's rhythm or muscle tissue. In this experiment, students will record their own EKG, identify the components, calculate heart rate, and observe how the tracing changes when the electrode leads are switched to simulate a myocardial infarction.
The document discusses electrocardiograms (EKGs) and how they are used to analyze the electrical activity of the heart. It provides the following key points:
1. An EKG records the electrical signals produced by the heart during each beat and can be used to identify components like the P, QRS, and T waves that correspond to different phases of the heartbeat.
2. Abnormalities in the shape, timing, or presence of these components can provide clues about potential heart conditions like arrhythmias, damage to heart muscle, or blockages.
3. The experiment involves using EKG sensors to record a subject's heartbeat over time, identifying the normal waveform components and calculating heart rate,
The document discusses electrocardiograms (EKGs) and how they are used to analyze the electrical activity of the heart. It provides the following key points:
1) An EKG records the electrical signals produced by the heart during each beat and can be used to identify components like the P, QRS, and T waves that correspond to different phases of the heartbeat.
2) Abnormalities in the shape, timing, or presence of these components can provide clues about potential heart conditions like arrhythmias, damage to heart muscle, or blockages.
3) The experiment involves using EKG sensors to record a subject's heartbeat over time, identifying the normal waveform components and calculating heart rate,
The document discusses electrocardiograms (EKGs) and how they are used to analyze the electrical activity of the heart. It provides the following key points:
- An EKG records the electrical events in the heart as it beats, showing the natural conduction pathways and contractions of the atria and ventricles.
- The different waves in an EKG (P, QRS, T) represent different stages of the heartbeat and can indicate heart conditions if abnormal.
- By placing electrodes in different positions, additional information can be gleaned from EKG tracings about the direction of electrical activity in the heart.
- Doctors can analyze EKG tracings for abnormalities that may indicate conditions like
2. investigation of cardiovascular system )2(Ahmad Hamadi
This document discusses electrocardiography (ECG) and its use in evaluating cardiac disease. An ECG records the electrical activity of the heart and can detect abnormalities in rhythm, conduction, chamber size and ischemia. A standard ECG involves 10 electrodes that produce 12 leads displaying the heart's electrical signals from different angles. ECGs are used to diagnose conditions like myocardial infarction and assess heart muscle damage through changes in the ST segment and T waves.
2. investigation of cardiovascular system )2(Ahmad Hamadi
This document discusses electrocardiography (ECG) and its use in evaluating cardiac disease. An ECG records the electrical activity of the heart and can detect abnormalities in rhythm, conduction, chamber size and ischemia. A standard ECG involves 10 electrodes that produce 12 leads displaying the heart's electrical signals from different angles. ECGs are used to diagnose conditions like myocardial infarction and assess heart muscle damage through changes in the ST segment and T waves.
This document discusses electrocardiograms (EKGs) and how they are used to analyze the electrical activity of the heart. It provides the following key points:
1. An EKG records the electrical signals produced by the heart during each beat and can be used to determine heart rate and identify any abnormalities.
2. The main components of an EKG waveform are labeled P, Q, R, S, and T and correspond to different stages of electrical conduction through the heart.
3. Doctors can examine EKG tracings to diagnose conditions like arrhythmias, heart attacks, or damage to heart muscle based on changes in waveforms and timing of intervals between components.
(1) An ECG records and displays the electrical activity of the heart over time using electrodes placed on the skin. It is used to evaluate cardiac rate, rhythm, and detect any abnormalities. (2) Key aspects of an ECG include the P wave, QRS complex, T wave, and intervals between them like the PR and QT. Together these provide information on depolarization and repolarization of the heart's chambers. (3) A standard 12-lead ECG positions 10 electrodes on the limbs and chest to measure electrical activity from multiple angles and identify any damage or disease.
An electrocardiogram (ECG) records the electrical activity of the heart. Small metal electrodes are attached to the skin on the arms, legs, and chest to detect electrical impulses from the heart. The ECG machine amplifies and records these impulses, showing normal and abnormal heart rhythms and any signs of heart damage or disease. A normal ECG tracing shows the P wave, QRS complex, and T wave representing atrial and ventricular contractions and repolarizations. The ECG test takes about five minutes and is painless.
The document discusses electrocardiograms (EKGs) and how they are used to analyze the electrical activity of the heart. It provides the following key points:
- An EKG records the electrical events in the heart as it beats, showing the natural conduction pathways and contractions of the atria and ventricles.
- The different waves in an EKG (P, QRS, T) represent different stages of the heartbeat and electrical conduction through the heart.
- Doctors can examine an EKG to check for abnormalities that may indicate heart conditions like arrhythmias, damage to heart muscle tissue, or heart attacks.
- In this experiment, students will record their own EKG, identify
An electrocardiogram (EKG or ECG) records the electrical activity of the heart over time. It shows different wave components including the P wave, QRS complex, and T wave that are associated with different events in the cardiac cycle. By analyzing the timing and appearance of these waves, healthcare professionals can detect abnormalities that may indicate disorders like arrhythmias, heart attacks, or damage to heart muscle tissue. This experiment uses an EKG sensor to record a subject's heartbeat and analyze the timing of waves to determine heart rate and the direction of electrical conduction in the ventricles.
Instrumental_and_Laboratory_Techniques_of_Examination_in_Pathology of CVS.pptHARSHIKARIZANI
Electrocardiography (ECG) is commonly used to examine the cardiovascular system. An ECG records and graphs the heart's electrical activity through electrodes placed on the skin. It is analyzed by assessing waves, intervals, rhythm and other characteristics to evaluate heart health and detect abnormalities. Various tests like Holter monitoring, exercise tests and pharmacological interventions further aid cardiovascular diagnosis.
This document provides an overview of electrocardiogram (ECG or EKG) interpretation presented by Ms. Hari Singh Nagar. It defines ECG as a test that records the heart's electrical activity over time using electrodes placed on the skin. The summary explains how to obtain an ECG by attaching electrodes, and how to interpret the waves, complexes, intervals and segments of an ECG strip including P wave, QRS complex, T wave, and others. It also describes how to determine the heart rate and rhythm from the ECG by measuring intervals between waves.
This document introduces a standardized method for electrocardiogram (ECG) interpretation. It begins by dedicating the document to Dr. Alan E. Lindsay, a master teacher of electrocardiography. It then outlines a 6 step method for ECG interpretation: 1) Measurements, 2) Rhythm analysis, 3) Conduction analysis, 4) Wave analysis, 5) Hypertrophy analysis, and 6) Miscellaneous abnormalities analysis. The document provides background information on the components of a 12-lead ECG and emphasizes following a systematic approach to avoid missing important abnormalities.
This document provides an introduction to electrocardiogram (ECG) interpretation. It outlines a standardized 6-step method for analyzing ECGs, including measurements, rhythm analysis, conduction analysis, waveform description, interpretation, and comparison to previous ECGs. The method emphasizes a systematic approach to avoid missing abnormalities. The document also reviews ECG waves, intervals, lead placements, and how to measure the frontal plane QRS axis.
This document summarizes two cases of patients with accessory pathways. In the first case, the patient presented with a delta wave on their ECG indicating a right-sided accessory pathway. Mapping and ablation were successful in isolating the pathway located in the posterior septal region of the right atrium. In the second case, the patient had a normal ECG but ablation of a left-sided anterior septal pathway terminated the arrhythmia induced by pacing. Both cases demonstrate the mapping and successful ablation of concealed accessory pathways.
This case report describes a 37-year-old man who presented with sudden onset severe left-sided neck pain and ST elevations on his ECG. He was incorrectly diagnosed with an anterior wall myocardial infarction and thrombolyzed. Further examination revealed differential blood pressures between his upper and lower extremities, suggesting an underlying aortic coarctation. Imaging confirmed severe coarctation of the aorta. The atypical presentation of neck pain and ECG changes were likely due to vasospasm and compression related to the coarctation. This case highlights the importance of a full clinical assessment prior to thrombolytic therapy to avoid unnecessary procedures.
This document discusses a study of 72 patients with bradycardia. Autonomic nervous system testing revealed autonomic dysfunction in most patients, with increased vagal tone being the most common finding present in 83.3% of patients. Several autonomic syndromes were also identified, with postural orthostatic tachycardia syndrome being present in 34.7% of patients. Treatment targeting the identified autonomic abnormalities improved symptoms in most patients. The study demonstrates that autonomic nervous system testing can help explain causes of bradycardia when clinical exams are otherwise normal.
More Related Content
Similar to A Mathematical Approach to Characterize Left Ventricular Hypertrophy from ECG Diagrams_Crimson Publishers
A M ODIFIED M ETHOD F OR P REDICTIVITY OF H EART R ATE V ARIABILITYcsandit
Heart Rate Variability (HRV) plays an important rol
e for reporting several cardiological and
non-cardiological diseases. Also, the HRV has a pro
gnostic value and is therefore quite
important in modelling the cardiac risk. The nature
of the HRV is chaotic, stochastic and it
remains highly controversial. Because the HRV has u
tmost importance, it needs a sensitive tool
to analyze the variability. In previous work, Rosen
stein and Wolf had used the Lyapunov
exponent as a quantitative measure for HRV detectio
n sensitivity. However, the two methods
diverge in determining the HRV sensitivity. This pa
per introduces a modification to both the
Rosenstein and Wolf methods to overcome their drawb
acks. The introduced Mazhar-Eslam
algorithm increases the sensitivity to HRV detectio
n with better accuracy.
The document discusses ECG signal analysis and abnormality detection using artificial neural networks. It defines normal and abnormal ECG signals, describing abnormalities like bradycardia and tachycardia. Two algorithms are described for detecting abnormalities: one analyzes heart rate and the other detects general heart diseases. An ANN system is used for ECG analysis and classification, taking spectral entropy, Poincare plot geometry, and largest Lyapunov exponent as inputs to classify eight cardiac conditions.
An electrocardiogram (EKG or ECG) records the electrical activity of the heart over time. It shows different wave components including the P wave, QRS complex, and T wave that represent the spread of electrical impulses through the heart's chambers and their contraction and relaxation. By analyzing the timing and appearance of these waves, doctors can detect abnormalities that may indicate heart conditions. In this experiment, students will use an EKG sensor to record their own heart activity, identify the wave components, and calculate their heart rate. They will also compare recordings from standard and alternate lead placements.
Case-1: ECG with Normal axis ; Case-2: ECG with left axis deviation
Case-3: ECG with extreme right axis deviation
Case-4: ECG with right axis deviation
Clinical significance of cardiac axis
What is Electrical Axis? Types of electrical axis
What are the Methods of ECG Axis Interpretation? How ECG axis can be determined?
How Ventricular (QRS) Axis is determined in Bundle Branch Blocks ?
What is Undetermined axis/ Indeterminate axis?
What are the causes of abnormal heart axis?
What are the causes of Right Axis Deviation(RAD)?
What are the causes of Left Axis Deviation?
What are the causes of Extreme Axis Deviation (indeterminate axis/ northwest axis)?
An electrocardiogram (ECG or EKG) records the electrical activity of the heart over time through electrodes placed on the skin. It shows five main components - P wave, QRS complex, and T wave - that represent the spread of electrical impulses through the heart during each heartbeat. Doctors can analyze features of the EKG like interval durations and waveform shapes to detect abnormalities and disorders of the heart's rhythm or muscle tissue. In this experiment, students will record their own EKG, identify the components, calculate heart rate, and observe how the tracing changes when the electrode leads are switched to simulate a myocardial infarction.
The document discusses electrocardiograms (EKGs) and how they are used to analyze the electrical activity of the heart. It provides the following key points:
1. An EKG records the electrical signals produced by the heart during each beat and can be used to identify components like the P, QRS, and T waves that correspond to different phases of the heartbeat.
2. Abnormalities in the shape, timing, or presence of these components can provide clues about potential heart conditions like arrhythmias, damage to heart muscle, or blockages.
3. The experiment involves using EKG sensors to record a subject's heartbeat over time, identifying the normal waveform components and calculating heart rate,
The document discusses electrocardiograms (EKGs) and how they are used to analyze the electrical activity of the heart. It provides the following key points:
1) An EKG records the electrical signals produced by the heart during each beat and can be used to identify components like the P, QRS, and T waves that correspond to different phases of the heartbeat.
2) Abnormalities in the shape, timing, or presence of these components can provide clues about potential heart conditions like arrhythmias, damage to heart muscle, or blockages.
3) The experiment involves using EKG sensors to record a subject's heartbeat over time, identifying the normal waveform components and calculating heart rate,
The document discusses electrocardiograms (EKGs) and how they are used to analyze the electrical activity of the heart. It provides the following key points:
- An EKG records the electrical events in the heart as it beats, showing the natural conduction pathways and contractions of the atria and ventricles.
- The different waves in an EKG (P, QRS, T) represent different stages of the heartbeat and can indicate heart conditions if abnormal.
- By placing electrodes in different positions, additional information can be gleaned from EKG tracings about the direction of electrical activity in the heart.
- Doctors can analyze EKG tracings for abnormalities that may indicate conditions like
2. investigation of cardiovascular system )2(Ahmad Hamadi
This document discusses electrocardiography (ECG) and its use in evaluating cardiac disease. An ECG records the electrical activity of the heart and can detect abnormalities in rhythm, conduction, chamber size and ischemia. A standard ECG involves 10 electrodes that produce 12 leads displaying the heart's electrical signals from different angles. ECGs are used to diagnose conditions like myocardial infarction and assess heart muscle damage through changes in the ST segment and T waves.
2. investigation of cardiovascular system )2(Ahmad Hamadi
This document discusses electrocardiography (ECG) and its use in evaluating cardiac disease. An ECG records the electrical activity of the heart and can detect abnormalities in rhythm, conduction, chamber size and ischemia. A standard ECG involves 10 electrodes that produce 12 leads displaying the heart's electrical signals from different angles. ECGs are used to diagnose conditions like myocardial infarction and assess heart muscle damage through changes in the ST segment and T waves.
This document discusses electrocardiograms (EKGs) and how they are used to analyze the electrical activity of the heart. It provides the following key points:
1. An EKG records the electrical signals produced by the heart during each beat and can be used to determine heart rate and identify any abnormalities.
2. The main components of an EKG waveform are labeled P, Q, R, S, and T and correspond to different stages of electrical conduction through the heart.
3. Doctors can examine EKG tracings to diagnose conditions like arrhythmias, heart attacks, or damage to heart muscle based on changes in waveforms and timing of intervals between components.
(1) An ECG records and displays the electrical activity of the heart over time using electrodes placed on the skin. It is used to evaluate cardiac rate, rhythm, and detect any abnormalities. (2) Key aspects of an ECG include the P wave, QRS complex, T wave, and intervals between them like the PR and QT. Together these provide information on depolarization and repolarization of the heart's chambers. (3) A standard 12-lead ECG positions 10 electrodes on the limbs and chest to measure electrical activity from multiple angles and identify any damage or disease.
An electrocardiogram (ECG) records the electrical activity of the heart. Small metal electrodes are attached to the skin on the arms, legs, and chest to detect electrical impulses from the heart. The ECG machine amplifies and records these impulses, showing normal and abnormal heart rhythms and any signs of heart damage or disease. A normal ECG tracing shows the P wave, QRS complex, and T wave representing atrial and ventricular contractions and repolarizations. The ECG test takes about five minutes and is painless.
The document discusses electrocardiograms (EKGs) and how they are used to analyze the electrical activity of the heart. It provides the following key points:
- An EKG records the electrical events in the heart as it beats, showing the natural conduction pathways and contractions of the atria and ventricles.
- The different waves in an EKG (P, QRS, T) represent different stages of the heartbeat and electrical conduction through the heart.
- Doctors can examine an EKG to check for abnormalities that may indicate heart conditions like arrhythmias, damage to heart muscle tissue, or heart attacks.
- In this experiment, students will record their own EKG, identify
An electrocardiogram (EKG or ECG) records the electrical activity of the heart over time. It shows different wave components including the P wave, QRS complex, and T wave that are associated with different events in the cardiac cycle. By analyzing the timing and appearance of these waves, healthcare professionals can detect abnormalities that may indicate disorders like arrhythmias, heart attacks, or damage to heart muscle tissue. This experiment uses an EKG sensor to record a subject's heartbeat and analyze the timing of waves to determine heart rate and the direction of electrical conduction in the ventricles.
Instrumental_and_Laboratory_Techniques_of_Examination_in_Pathology of CVS.pptHARSHIKARIZANI
Electrocardiography (ECG) is commonly used to examine the cardiovascular system. An ECG records and graphs the heart's electrical activity through electrodes placed on the skin. It is analyzed by assessing waves, intervals, rhythm and other characteristics to evaluate heart health and detect abnormalities. Various tests like Holter monitoring, exercise tests and pharmacological interventions further aid cardiovascular diagnosis.
This document provides an overview of electrocardiogram (ECG or EKG) interpretation presented by Ms. Hari Singh Nagar. It defines ECG as a test that records the heart's electrical activity over time using electrodes placed on the skin. The summary explains how to obtain an ECG by attaching electrodes, and how to interpret the waves, complexes, intervals and segments of an ECG strip including P wave, QRS complex, T wave, and others. It also describes how to determine the heart rate and rhythm from the ECG by measuring intervals between waves.
This document introduces a standardized method for electrocardiogram (ECG) interpretation. It begins by dedicating the document to Dr. Alan E. Lindsay, a master teacher of electrocardiography. It then outlines a 6 step method for ECG interpretation: 1) Measurements, 2) Rhythm analysis, 3) Conduction analysis, 4) Wave analysis, 5) Hypertrophy analysis, and 6) Miscellaneous abnormalities analysis. The document provides background information on the components of a 12-lead ECG and emphasizes following a systematic approach to avoid missing important abnormalities.
This document provides an introduction to electrocardiogram (ECG) interpretation. It outlines a standardized 6-step method for analyzing ECGs, including measurements, rhythm analysis, conduction analysis, waveform description, interpretation, and comparison to previous ECGs. The method emphasizes a systematic approach to avoid missing abnormalities. The document also reviews ECG waves, intervals, lead placements, and how to measure the frontal plane QRS axis.
This document summarizes two cases of patients with accessory pathways. In the first case, the patient presented with a delta wave on their ECG indicating a right-sided accessory pathway. Mapping and ablation were successful in isolating the pathway located in the posterior septal region of the right atrium. In the second case, the patient had a normal ECG but ablation of a left-sided anterior septal pathway terminated the arrhythmia induced by pacing. Both cases demonstrate the mapping and successful ablation of concealed accessory pathways.
Similar to A Mathematical Approach to Characterize Left Ventricular Hypertrophy from ECG Diagrams_Crimson Publishers (20)
This case report describes a 37-year-old man who presented with sudden onset severe left-sided neck pain and ST elevations on his ECG. He was incorrectly diagnosed with an anterior wall myocardial infarction and thrombolyzed. Further examination revealed differential blood pressures between his upper and lower extremities, suggesting an underlying aortic coarctation. Imaging confirmed severe coarctation of the aorta. The atypical presentation of neck pain and ECG changes were likely due to vasospasm and compression related to the coarctation. This case highlights the importance of a full clinical assessment prior to thrombolytic therapy to avoid unnecessary procedures.
This document discusses a study of 72 patients with bradycardia. Autonomic nervous system testing revealed autonomic dysfunction in most patients, with increased vagal tone being the most common finding present in 83.3% of patients. Several autonomic syndromes were also identified, with postural orthostatic tachycardia syndrome being present in 34.7% of patients. Treatment targeting the identified autonomic abnormalities improved symptoms in most patients. The study demonstrates that autonomic nervous system testing can help explain causes of bradycardia when clinical exams are otherwise normal.
The study objective was to evaluate the cardioprotective activity of Biofield Energized test item (DMEM) in rat cardiomyocytes (H9c2) cells. The test item (DMEM medium) was divided into three parts, first part received one-time Consciousness Energy Healing Treatment by a renowned Biofield Energy Healer, Dahryn Trivedi and was labeled as the one-time Biofield Energy Treated (BT-I) DMEM, while second part received the two-times Biofield Energy Treatment and is denoted as BT-II DMEM.
Essential hypertension, the most common type, is an important cause of morbidity and mortality in the elderly, a rapidly growing section of the population. It is a sad reality that until the 1950s treating benign hypertension was not thought to be necessary. The tragic death of Franklin Delano Roosevelt on April 12, 1945 at the age of 63 years, with a blood pressure of 350/195mmHg, and without treatment shocked the healthcare community.
This document presents an optimization of algorithms for real-time ECG beat classification. It compares algorithms using voltage values in the time domain versus those using Daubechies wavelet analysis. It extracts features around reference peaks within the QRS complex and uses clustering methods to classify beats in real-time as normal, premature ventricular contraction, or unclassified. Evaluating algorithms on 32 MIT-BIH records, the method using Daubechies wavelets and correlation measure achieved 93.25% sensitivity and 91.43% positive predictivity for premature ventricular contraction detection, making it suitable for real-time systems due to low computational cost.
Coronary artery diseases (CAD) known as atherosclerotic heart disease, atherosclerotic cardiovascular disease, coronary heart disease (CHD), or ischemic heart disease (IHD). CAD is the largest contributor of cardiovascular diseases (CVDs) and mortality rate is due in prevalence to atherosclerosis, a chronic inflammatory condition of the arterial wall. Unfortunately, myocardial infarction (MI) is still a first common manifestation of CHD and, in about 50% of patients; angina pectoris is the first symptom of the pathology.
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2. How to cite this article: Srijan S, Uttam G, Susmita S, Shantanu D. A Mathematical Approach to Characterize Left Ventricular Hypertrophy from ECG Diagrams.
Open J Cardiol Heart Dis. 1(2). OJCHD.000509. 2018. DOI: 10.31031/OJCHD.2018.01.000509
Open Journal of Cardiology & Heart Diseases
2/5
Open J Cardiol Heart Dis
Volume 1 - Issue - 2
LVH are:
i. Feeling short of breath,
ii. Chest pain, especially after activity,
iii. Feeling dizzy or fainting,
iv. Rapid heartbeat, or a pounding or fluttering sensation in
chest.
ECG of LVH (in doctor’s view)
Left ventricular hypertrophy causes a tall R wave (>25mm) in
lead V5 or V6, a deep S wave in lead V1 or V2, inverted T wave in
leads I, II, AVL, V5, V6, sometimes V4 and R waves in lead V5 or
V6 plus S wave in lead V1 or V2 greater than 35 mm. It is difficult
to diagnose minor degrees of left ventricular hypertrophy from the
ECG [10].
Modified definitions of Riemann-Liouville derivative
The basic definitions of fractional derivatives are of Riemann-
Liouville (R-L) [2], Caputo [8], and Jumarie [11]. To overcome the
shortcoming of the R-L definition that derivative of a constant is
non-zero which is contradiction of the conventional integer order
calculus, Jumarie [11] first revised the R-L definition of fractional
derivative in the following form.
( )
1
0
0
( )
( )
1
( ) ( ) ( ) ,for 0
( )
1
( ) [ ( ) (0)] ,for 0 1
(1 )
( ) for 1, 1.
x
x
x
n
n
D f x x f d
d
x f f d
dx
f x n n n
α α
α
α
ξ ξ ξ α
α
ξ ξ ξ α
α
α
− −
−
−
= − <
Γ −
= − − < <
Γ −
= ≤ < + ≥
∫
∫
The above definition [11] is developed using left R-L derivative.
Similarly modification has also been developed by us using the
right R-L derivative [9]. Note in the above definition for negative
fractional orders the expression is just Riemann-Liouvelli fractional
integration. The modification is carried out in the R-L derivative
formula, for the positive fractional orders alpha. The idea of this
modification is to remove the offset value of function at start point
of the fractional derivative from the function, and carry out R-L
derivative as usually done for the function [9].
Unreachable function and graphs
Figure 1: A normal shape of PQRST wave in ECG.
There are many functions which are everywhere continuous
but not-differentiable at some points or at all points. These
functions are known as unreachable functions [11]. The function (i)
is unreachable at the point .This means they have no integer order
derivativeat buthave orderderivativeatthatpoint[1]. Unreachable
graphs are diagrammatic representation of unreachable functions.
The ECG graphs are such types of unreachable graphs. They have
unreachable points Q, R, S in the ‘PQRST’ wave at which classical
derivatives do not exist but fractional derivatives exist. In this paper
we have used Q, R, S as points though they are wave of ECG shown
in Figure 1.
Phase transition
We define the phase transition at a non-differentiable point
of a continuous graph as the difference between the left and right
modified R-L derivatives at that point.
Fractional Calculus Technique for Characterizing Left
Ventricular Hypertrophy
In this section we shall describe the fractional calculus
technique for characterizing left ventricular hypertrophy from ECG
diagrams. This mathematical technique is used to calculate both
left and right fractional derivatives and hence the phase transitions
at the Q, R, S points of the QRS complexes of the V1, V2, V5 and
V6 leads of ECG graphs. For this purpose first we take two points
say Q1 at above of the Q point on QRS complex and say S1 after
the point S on the same QRS complex of the ECG. So we can fit
three straight lines with five points Q1
, Q, R, S, S1
in which three
non-differential points are present. This case arises many times in
ECG leads. Due to this purpose we have to calculate left and right
fractional derivative together with corresponding phase transition
value at the unreachable points of ECG leads. Thus we construct the
newly formed theorem as
Theorem
. Let us consider the function
,
( )
,
ax b p x q
f x
cx d q x r
+ ≤ ≤
=
+ ≤ ≤
with It is continuous at x=q such that but not differentiable at
that point. Then left fractional derivative, right fractional derivative
and phase transition at that point x=q are respectively:
( )
1 1
( ) ( )
1 1
( ) ( )
( ) , ( ) ;
(2 ) (2 )
( ) ( )
.
(2 )
L R
a q p c r q
f q f q
a q p c r q
PT
α α
α α
α α
α α
α
− −
− −
− −
= =
Γ − Γ −
− − −
=
Γ −
In the above theorem we consider a function which is linear in
both sides of non-differentiable point x=q. Similarly sometimes any
one or both the segments say P1Q and QR are nonlinear. In those
cases similar type of theorems are constructed to evaluate left
and right fractional derivative together with corresponding phase
transition value at the unreachable points of ECG leads to analyze
the ECG graphs. All these cases have to be used in this paper in next
section.
Applications of Fractional Derivative in ECG Graphs
Now we shall characterize the ECG graphs by the help of
fractional derivative and compare normal ECGs with abnormal
3. Open Journal of Cardiology & Heart Diseases
How to cite this article: Srijan S, Uttam G, Susmita S, Shantanu D. A Mathematical Approach to Characterize Left Ventricular Hypertrophy from ECG Diagrams.
Open J Cardiol Heart Dis. 1(2). OJCHD.000509. 2018. DOI: 10.31031/OJCHD.2018.01.000509
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Open J Cardiol Heart Dis
Volume 1 - Issue - 2
ECGs (LVH). For this purpose we shall consider ½- order fractional
derivatives. The non-differentiable points Q, R, S of QRS complexes
of PQRST wave of any leads are used here usually points, not as
wave. Also we shall calculate the fractal dimension of the considered
leads of ECG graphs. If Q or S point is not prominent at QRS complex
of any lead of the ECGs under consideration then we cannot find
the Left Fractional Derivative and Right Fractional Derivative at
that point. We have denoted those cases by ‘NA’ i.e. ‘Not Arise’. To
investigate the characteristics of the ECG we here consider normal
ECG and problematic ECG (in our case LVH ECG to be compared
with normal ECG).
Since LVH is characterized by deep S wave in V1 and V2 leads
and long R wave in V5 and V6 leads. So our concern to find any
distinguishing measurements of P.T values at non-differentiable
points on S wave in V1 and V2 and R wave in V5 and V6 leads
to characterize the problematic ECG (in our case LVH) with
normal ECG. Thus our paper contributed only P.T. values at non-
differentiable points at those leads for LVH ECGs. So our concern
to find any distinguishing measurements of P.T values at non-
differentiable points on S wave in V1 and V2 and R wave in V5 and
V6 leads to characterize the problematic ECG (in our case LVH) with
normal ECG. Following tables are new and constructed from our
fractional calculus methodology.
Characterization ECG
The considerable methodology which is now used for normal
ECG as well as for problematic ECG (LVH) [12] also shown to help
us a strong comparison between Normal ECGs and LVH ECGs in this
section.
Table 1A: Length of different parts of ECG: A=Length of S wave
(mm) in V1 lead, B=Length of S wave (mm) in V2 lead ,C=Length
of R wave (mm) in V5 lead, D=Length of R wave (mm) in V6 lead
respectively.
Normal ECG sample Problematic ECG sample
PQRST Waves A B C D PQRST Waves A B C D
1st
9.5 21.5 18 14.5 1st
12 27 56 56.5
2nd
10.5 23 18 14.5 2nd
11 25 54.1 56
3rd
18 13.5 3rd
59 53.2
E=A+C F=A+D G=B+C H=B+D E=A+C F=A+D G=B+C H=B+D
27.5 24 39.5 36 68 68.5 83 83.5
27.5 24 39.5 36 66.1 68 81.1 83
27.5 23 39.5 35 71 65.2 86 80.2
28.5 25 41 37.5 67 67.5 81 81.5
28.5 25 41 37.5 65.1 67 79.1 81
28.5 24 41 36.5 70 64.2 84 78.2
Here, we see that in Table 1A lengths of S and R wave in V1, V2
and V5, V6 respectively are all greater than 25mm except length of
S wave in V1 lead for problematic ECG, these measurement is below
25mm for normal ECG and length of E,F,G and H are all greater
than 35mm of that table for problematic ECG, these measurement
is also below for normal ECG. So from Doctor’s point of view
this patient with problematic ECG has cardiac problem which
called Left Ventricular Hypertrophy. Now we have to calculate
above mentioned techniques to characterize ECGs for comparing
problematic ECG with normal ECG given below Table 1B & Table 1C.
4. How to cite this article: Srijan S, Uttam G, Susmita S, Shantanu D. A Mathematical Approach to Characterize Left Ventricular Hypertrophy from ECG Diagrams.
Open J Cardiol Heart Dis. 1(2). OJCHD.000509. 2018. DOI: 10.31031/OJCHD.2018.01.000509
Open Journal of Cardiology & Heart Diseases
4/5
Open J Cardiol Heart Dis
Volume 1 - Issue - 2
Table 1B: Phase transition at the non-differentiable points Q,R,S of V1,V2,V5 and V6 leads of Normal ECG sample.
P.T. values of V1 P.T. values of V2 P.T. values of V5 P.T. values of V6
1st
For PQ:QR at Q 6.383076 NA 30.244018 25.489442
For QR:RS at R 21.542883 34.4156 62.234996 40.064340
For RS:ST at S 25.532306 44.2073 36.896290 20.117226
2nd
For PQ:QR at Q 5.077706 10.1554 30.319613 21.243420
For QR:RS at R 21.833282 46.8581 52.419806 42.829167
For RS:ST at S 24.734422 57.4477 28.483269 25.239477
3rd
For PQ:QR at Q 31.915382 23.823144
For QR:RS at R 61.437111 37.340191
For RS:ST at S 35.534215 18.190962
Table 1C: Phase transition at the non-differentiable points Q, R, S of V1, V2, V5 and V6 leads of Problematic ECG (LVH) sample.
P.T. values of V1 P.T. values of V2 P.T. values of V5 P.T. values of V6
1st
For PQ:QR at Q NA 15.1388 62.1737 62.5706
For QR:RS at R 15.2332 49.2011 141.7848 118.2342
For RS:ST at S 18.0541 40.8057 81.8757 NA
2nd
For PQ:QR at Q NA 12.3608 61.1582 60.0624
For QR:RS at R 15.1027 39.2575 135.0026 115.2309
For RS:ST at S 16.7741 36.9892 81.0753 NA
3rd
For PQ:QR at Q 62.2868 55.1727
For QR:RS at R 142.2155 185.3884
For RS:ST at S 84.8053 NA
Discussion
In this paper we have studied characteristics of normal ECG
graphs and ECG graphs of LVH patients, by finding fractional
derivatives at non-differentiable points. From the above table (1B-
C) it is observed that Phase Transition (P.T) values are maximum
at the point R and S of QRS complexes at V1, V2 and V5, V6 leads
of problematic ECG respectively. We have recorded and compared
the P.T values at the point R and S of V1, V2 and V5, V6 leads of
different ECG leads. The P.T. values of different non-differentiable
points of the V1, V2, V5, V6 leads in normal ECG are less than 50.
For values 50 to 65 the patients are prone to LVH where as patients
having P.T. values above 65 in the V1, V2, V5, V6 leads are suffering
from LVH problem. But these ranges are not present in many cases
such as if there are any other problem together with LVH; also if the
nature of any lead behaves like a normal ECG lead (since ECG do
not found any disease at first or minor stage in ECG tracing paper
many times). In those case Doctors will decide to do another tests
like ECO, TMT, Angiography of the patient to detect exact problem
of that patient. The values of P.T. of normal ECG leads for different
non-differentiable points are low but it increases abruptly for
LVH patients. From our samples we can conclude that if the phase
transition value is greater than 50 then the person will be in danger
zone. Thus by studying large number of ECG it is possible to find
the a suitable range for the fractal dimension of the ECG leads and
phase transition (P.T) values at the non-differentiable points that
will help the doctors to determine the LVH conditions of patients.
We will report other ailments in our next study. However, this type
of study is not reported elsewhere. This method is a new method
we are reporting for the first time-could be an aid for differential
diagnostics in medical science.
Compliance with Ethical Standards
Authors declare that none of them have any conflict of interest.
Ethical Approval
All ECG have been downloaded from internet.
Acknowledgement
Authors thank Dr. Tridip Sengupta, Ex-Senior Medical Officer
Cardiology, R. G. Kar Medical College & Hospital, Kolkata, and Dr.
Manoranjan Mandal, Department of Cardiology, N. R. S. Medical
College, Kolkata, for their valuable guidance in understanding ECG
graphs from medical point of view, and encouragement on this
new idea to have a characterization studies for ECG. The authors
are grateful to the anonymous referee for a careful checking of the
details and for helpful comments that improved this paper.
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5. Open Journal of Cardiology & Heart Diseases
How to cite this article: Srijan S, Uttam G, Susmita S, Shantanu D. A Mathematical Approach to Characterize Left Ventricular Hypertrophy from ECG Diagrams.
Open J Cardiol Heart Dis. 1(2). OJCHD.000509. 2018. DOI: 10.31031/OJCHD.2018.01.000509
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Open J Cardiol Heart Dis
Volume 1 - Issue - 2
5. Loverro Adam (2004) Fractional Calculus: History, definitions and
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