scholarly journals Electrocardiographic surrogates of structural myocardial alterations in the Dorper sheep heart

2005 ◽  
Vol 72 (4) ◽  
Author(s):  
J. Ker ◽  
E.C. Webb
Keyword(s):  
Qrs Complex ◽  
Premature Ventricular Complexes ◽  
Cardiac Memory ◽  
St Segment ◽  
Electrocardiographic Markers ◽  
Dorper Sheep ◽  
Myocardial Pathology ◽  
T Waves

In this study we evaluated the validity of well-known human electrocardiographic markers of myocardial pathology in Dorper sheep. These markers include: the duration of the QRS complex of premature ventricular complexes (PVCs), the presence of notching of the QRS complex of PVCs and change of the ST-segment of PVCs. It was shown that these three electrocardiographic phenomena correlate with myocardial pathology in the hearts of Dorper sheep. We also describe a new electrocardiographic indicator of myocardial pathology, namely an increase in the frequency of cardiac memory T waves as a new electrocardiographic surrogate for myocardial pathology in the hearts of Dorper sheep.

scholarly journals Electrocardiographic surrogates of structural myocardial alterations in the Dorper sheep heart

2005 ◽  
Vol 72 (4) ◽  
pp. 273-277 ◽  
Author(s):  
J. Ker ◽  
E.C. Webb
Keyword(s):  
Qrs Complex ◽  
Premature Ventricular Complexes ◽  
Cardiac Memory ◽  
St Segment ◽  
Electrocardiographic Markers ◽  
Dorper Sheep ◽  
Myocardial Pathology ◽  
T Waves

In this study we evaluated the validity of well-known human electrocardiographic markers of myocardial pathology in Dorper sheep. These markers include: the duration of the QRS complex of premature ventricular complexes (PVCs), the presence of notching of the QRS complex of PVCs and change of the ST-segment of PVCs. It was shown that these three electrocardiographic phenomena correlate with myocardial pathology in the hearts of Dorper sheep. We also describe a new electrocardiographic indicator of myocardial pathology, namely an increase in the frequency of cardiac memory T waves as a new electrocardiographic surrogate for myocardial pathology in the hearts of Dorper sheep.

A Comprehensive Algorithm for the Analysis of ECG Waveforms

2012 ◽  
Author(s):  
Abdul Jaleel Palliyali ◽  
Reza Tafreshi ◽  
Nasreen Mohsin ◽  
Leyla Tafreshi
Keyword(s):  
Curve Fitting ◽  
Clinical Judgment ◽  
Qrs Complex ◽  
Average Accuracy ◽  
St Segment ◽  
Reliable Performance ◽  
Adaptive Thresholds ◽  
St Elevation ◽  
Automate Diagnosis ◽  
T Waves

This paper presents a comprehensive approach for the detailed analysis of ECG waveforms including various morphologies to aid clinical diagnosis. Clinical judgment is often based on observing various features which may occur simultaneously on the ECG. Thus, to automate diagnosis, a comprehensive tool capable of detecting all these features is required. Parabolic curve fitting, adaptive thresholds and synchronicity across leads are utilized to detect the various waves of the QRS complex namely Q,R,S,R’ and S’. Onset of the QRS complex and the J point are detected using a ‘modified second derivative’ approach. The isoelectric level is detected using linearity and slope conditions. P and T waves are detected using ‘area under curve’ approach. Measurements such as peak-to-peak intervals and ST elevation/depression are numerically calculated from the points obtained. Curve fitting and change in slope are utilized for obtaining morphology of the ST segment. Presence of significant Q waves and abnormal T waves are inferred using clinical guidelines and numerical calculations. The performance of the algorithm is validated on 40 sample patient data — 20 healthy and 20 with Myocardial Infarction. Average accuracy shown in detecting all points of interest is 98.5%. All measurements are successfully calculated from these points. Along with this reliable performance, the approach proves to be simple and computationally fast.

scholarly journals Electrocardiographic changes in awassi diarrheic suckling lambs in Iraq

2019 ◽  
Vol 43 (1) ◽  
pp. 26-33
Author(s):  
Islam Jawad . Alkhafaji
Keyword(s):  
P Wave ◽  
Qrs Complex ◽  
Sinus Arrhythmia ◽  
T Wave ◽  
St Depression ◽  
St Segment ◽  
Electrocardiographic Changes ◽  
Qrs Duration ◽  
Awassi Lambs ◽  
T Waves

This study was done to investigate the electrocardiographic changes in 90 diarrheic nursed Awassi lambs, in comparison with 10 clinically healthy lambs of the same breed. Their ages were ranged from 5 days to 2 months, in Karbala City-Iraq, from November 2015 to April 2016. The  diarrheic lambs showed significant (P≤0.05) decreased duration of  P-wave (0.039±0.0000001 ms and shorter QRS wave amplitudes 0.6 0±0.042 mV with  duration 0.041±0.0008 ms  , higher T wave amplitude and   duration (  0.25±0.034 mV  and 0.070±0.002 ms)  , prolonged QT (0.21±0.004 ms) but  ST-segment  ( 0.17±0.004 ms) were its observed  sinus arrhythmia with tachycardia in  lead-II  in diarrheic lambs were recorded  compared with  non-diarrheic lambs group which their QRS duration and amplitude were it was (0.04±0.000001ms and 0.65±0.026 mV ) , T waves duration and amplitude were (  0.076±0.004 ms and 0.21±0.012 mV  )   QT interval (0.20±0.011 ms) and ST-segment (  0.16±0.011 ms) .The morphological abnormal of ECG changes in diarrheic suckling lambs characterized by a widening or flattening, bifid(mitral) and pulmonale (tall) shape  of P wave, increased P-R interval, increased duration of QRS complex and QT-prolongation, ST-depression or elevation .Inverted or board (slurring) tall, symmetric, peaked shape of T waves. These abnormal shapes appeared alternately   in lead I, II, III, aVR, aVL and aVF. Conclusively the diarrheic lambs showed serious abnormal changes of electrocardiography..

A PVC BEATS RECOGNITION USING FUZZY CLASSIFIER

2010 ◽  
Vol 10 (02) ◽  
pp. 327-339
Author(s):  
M. A. CHIKH ◽  
OMAR BEHADADA
Keyword(s):  
Qrs Complex ◽  
Fuzzy Classifier ◽  
Premature Ventricular Complexes ◽  
Rr Interval

This article describes a fuzzy classifier for the identification of premature ventricular complexes (PVCs) in surface electrocardiograms (ECGs). The classifier uses features extracted from the ECG beat, such as the width of QRS complex and RR interval. The performance of the algorithm is evaluated on the MIT-BIH Arrhythmia Database following the AAMI recommendations. The results of the experiments of the recognition of PVCs have confirmed the reliability and advantage of the proposed approach.

scholarly journals Evaluation of the Mandibular Incisive Canal by Panoramic Radiography and Cone-Beam Computed Tomography

2018 ◽  
pp. 1-13
Author(s):  
Pablo E Tauber ◽  
Virginia Mansilla ◽  
Pedro Brugada ◽  
Sara S Sánchez P ◽  
Stella M Honoré ◽  
...  
Keyword(s):  
Right Ventricular Outflow Tract ◽  
Ventricular Outflow Tract ◽  
Qrs Complex ◽  
Incisive Canal ◽  
St Segment Elevation ◽  
Longitudinal Plane ◽  
St Segment ◽  
Endocardial Mapping ◽  
The Right

Background: Radiofrequency ablation (RFA) in Brugada syndrome (BrS) has been performed both endocardially and epicardially. The substrate in BrS is thus unclear. Objectives: To investigate the functional endocardial substrate and its correlation with clinical, electrophysiological and ECG findings in order to guide an endocardial ablation. Methods: Thirteen patients (38.7±12.3 years old) with spontaneous type 1 ECG BrS pattern, inducible VF with programmed ventricular stimulation (PVS) and syncope without prodromes were enrolled. Before to endocardial mapping the patients underwent flecainide testing with the purpose of measuring the greatest ST-segment elevation for to be correlated with the size and location of substrate in the electro-anatomic map. Patients underwent endocardial bipolar and electro-anatomic mapping with the purpose of identify areas of abnormal electrograms (EGMs) as target for RFA and determine the location and size of the substrate. Results: When the greatest ST-segment elevation was in the 3rd intercostal space (ICS), the substrate was located upper in the longitudinal plane of the right ventricular outflow tract (RVOT) and a greatest ST-segment elevation in 4th ICS correspond with a location of substrate in lower region of longitudinal plane of RVOT. A QRS complex widening on its initial and final part, with prolonged transmural and regional depolarization time of RVOT corresponded to the substrate locateded in the anterior-lateral region of RVOT. A QRS complex widening rightwards and only prolonged transmural depolarization time corresponded with a substrate located in the anterior, anterior-septal or septal region of RVOT. RFA of endocardial substrate suppressed the inducibility and ECG BrS pattern during 34.7±15.5 months. After RFA, flecainide testing confirmed elimination of the ECG BrS pattern. Endocardial biopsy showed a correlation between functional and ultrastructural alterations in two patients.

Arrhythmogenic Mechanisms

1992 ◽  
Vol 3 (1) ◽  
pp. 157-165 ◽  
Author(s):  
Terri Abraham
Keyword(s):  
Sinus Node ◽  
Cardiac Cells ◽  
Surrounding Tissue ◽  
Qrs Complex ◽  
Contributing Factors ◽  
Electrical Currents ◽  
Electrolyte Disturbance ◽  
St Segment ◽  
Low Amplitude ◽  
Reentrant Circuit

The arrhythmogenic mechanisms are the basis for the genesis of a wide variety of complex dysrhythmias that can arise in both pacemaker and nonpacemaker cells. Automaticity, or the ability to rhythmically and spontaneously depolarize cardiac cells, is normally the domain of the sinus node. Altered automaticity takes place when conduction is enhanced or abnormal. A second mechanism, reentry, refers to a phenomenon that occurs when an impulse is delayed within a pathway of slow conduction and then reenters surrounding tissue and produces another impulse. One-way conduction is necessary to produce a return route for the reentrant circuit. Lastly, late potentials are fragmented, low-amplitude electrical currents that occur at the terminal portion of the QRS complex or during the ST segment. Supraventricular and ventricular beats and tachydysrhythmias are the consequences of these mechanisms. Common contributing factors include but are not limited to hypoxia, hypercapnia, electrolyte disturbance, catecholamines, and pharmacotherapy

Imaging QRS complex and ST segment in myocardial infarction

2014 ◽  
Vol 47 (4) ◽  
pp. 438-447 ◽  
Author(s):  
Ljuba Bacharova ◽  
Lia E. Bang ◽  
Vavrinec Szathmary ◽  
Anton Mateasik
Keyword(s):  
Myocardial Infarction ◽  
Qrs Complex ◽  
St Segment

ECG SIGNAL GENERATION AND HEART RATE VARIABILITY SIGNAL EXTRACTION: SIGNAL PROCESSING, FEATURES DETECTION, AND THEIR CORRELATION WITH CARDIAC DISEASES

2012 ◽  
Vol 12 (04) ◽  
pp. 1240012 ◽  
Author(s):  
GOUTHAM SWAPNA ◽  
DHANJOO N. GHISTA ◽  
ROSHAN JOY MARTIS ◽  
ALVIN P. C. ANG ◽  
SUBBHURAAM VINITHA SREE
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Sinus Bradycardia ◽  
Premature Ventricular Contraction ◽  
P Wave ◽  
Ecg Signal ◽  
Qrs Complex ◽  
T Wave ◽  
St Segment ◽  
Cardiac Disorders

The sum total of millions of cardiac cell depolarization potentials can be represented by an electrocardiogram (ECG). Inspection of the P–QRS–T wave allows for the identification of the cardiac bioelectrical health and disorders of a subject. In order to extract the important features of the ECG signal, the detection of the P wave, QRS complex, and ST segment is essential. Therefore, abnormalities of these ECG parameters are associated with cardiac disorders. In this work, an introduction to the genesis of the ECG is given, followed by a depiction of some abnormal ECG patterns and rhythms (associated with P–QRS–T wave parameters), which have come to be empirically correlated with cardiac disorders (such as sinus bradycardia, premature ventricular contraction, bundle-branch block, atrial flutter, and atrial fibrillation). We employed algorithms for ECG pattern analysis, for the accurate detection of the P wave, QRS complex, and ST segment of the ECG signal. We then catagorited and tabulated these cardiac disorders in terms of heart rate, PR interval, QRS width, and P wave amplitude. Finally, we discussed the characteristics and different methods (and their measures) of analyting the heart rate variability (HRV) signal, derived from the ECG waveform. The HRV signals are characterised in terms of these measures, then fed into classifiers for grouping into categories (for normal subjects and for disorders such as cardiac disorders and diabetes) for carrying out diagnosis.

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