Intelligent Classifier for Atrial Fibrillation (ECG)

This chapter is focused on the analysis and classification of arrhythmias. An arrhythmia is any cardiac pace that is not the typical sinusoidal one due to alterations in the formation and/or transportation of the impulses. In pathological conditions, the depolarization process can be initiated outside the sinoatrial (SA) node and several kinds of extra-systolic or ectopic beatings can appear. Besides, electrical impulses can be blocked, accelerated, deviated by alternate trajectories and can change its origin from one heart beat to the other, thus originating several types of blockings and anomalous connections. In both situations, changes in the signal morphology or in the duration of its waves and intervals can be produced on the ECG, as well as a lack of one of the waves. This work is focused on the development of intelligent classifiers in the area of biomedicine, focusing on the problem of diagnosing cardiac diseases based on the electrocardiogram (ECG), or more precisely on the differentiation of the types of atrial fibrillations. First of all we will study the ECG, and the treatment of the ECG in order to work with it, with this specific pathology. In order to achieve this we will study different ways of elimination, in the best possible way, of any activity that is not caused by the auriculars. We will study and imitate the ECG treatment methodologies and the characteristics extracted from the electrocardiograms that were used by the researchers that obtained the best results in the Physionet Challenge, where the classification of ECG recordings according to the type of Atrial Fibrillation (AF) that they showed, was realised. We will extract a great amount of characteristics, partly those used by these researchers and additional characteristics that we consider to be important for the distinction mentioned before. A new method based on evolutionary algorithms will be used to realise a selection of the most relevant characteristics and to obtain a classifier that will be capable of distinguishing the different types of this pathology.

Download Full-text

Monoclonal Antibodies That Distinguish Antigenic Variants of Canine Parvovirus

Clinical and Diagnostic Laboratory Immunology ◽

10.1128/cdli.10.6.1085-1089.2003 ◽

2003 ◽

Vol 10 (6) ◽

pp. 1085-1089 ◽

Cited By ~ 11

Author(s):

Masato Nakamura ◽

Kazuya Nakamura ◽

Takayuki Miyazawa ◽

Yukinobu Tohya ◽

Masami Mochizuki ◽

...

Keyword(s):

Monoclonal Antibodies ◽

Antigenic Site ◽

Canine Parvovirus ◽

The Other ◽

Escape Mutants ◽

Feline Parvovirus ◽

Resistant Mutants ◽

Selection Of

ABSTRACT Canine parvovirus (CPV) is classified as a member of the feline parvovirus (FPV) subgroup. CPV isolates are divided into three antigenic types: CPV type 2 (CPV-2), CPV-2a, and CPV-2b. Recently, new antigenic types of CPV were isolated from Vietnamese leopard cats and designated CPV-2c(a) or CPV-2c(b). CPV-2c viruses were distinguished from the other antigenic types of the FPV subgroup by the absence of reactivity with several monoclonal antibodies (MAbs). To characterize the antigenicity of CPV-2c, a panel of MAbs against CPV-2c was generated and epitopes recognized by these MAbs were examined by selection of escape mutants. Four MAbs were established and classified into three groups on the basis of their reactivities: MAbs which recognize CPV-2a, CPV-2b, and CPV-2c (MAbs 2G5 and 20G4); an MAb which reacts with only CPV-2b and CPV-2c(b) (MAb 21C3); and an MAb which recognizes all types of the FPV subgroup viruses (MAb 19D7). The reactivity of MAb 20G4 with CPV-2c was higher than its reactivities with CPV-2a and CPV-2b. These types of specificities of MAbs have not been reported previously. A mapping study by analysis of neutralization-resistant mutants showed that epitopes recognized by MAbs 21C3 and 19D7 belonged to antigenic site A. Substitution of the residues in site B and the other antigenic site influenced the epitope recognized by MAb 2G5. It was suggested that the epitope recognized by MAb 20G4 was related to antigenic site B. These MAbs are expected to be useful for the detection and classification of FPV subgroup isolates.

Download Full-text

Disease Classification Using ECG Signals Based on R-Peak Analysis With ABC and ANN

International Journal of Electronics, Communications, and Measurement Engineering ◽

10.4018/ijecme.2019070105 ◽

2019 ◽

Vol 8 (2) ◽

pp. 67-86 ◽

Cited By ~ 1

Author(s):

Suman Lata ◽

Rakesh Kumar

Keyword(s):

Feature Extraction ◽

Comparative Analysis ◽

Classification Accuracy ◽

Disease Classification ◽

Cardiac Diseases ◽

Ecg Signals ◽

Processing Steps ◽

Ann Classification ◽

Selection Of

ECG feature extraction has an important role in identifying a number of cardiac diseases. Lots of work has been done in this field but the most important challenges faced in previous work are the selection of proper R-peaks and R-R intervals due to the lack of appropriate pre-processing steps like decomposition, smoothing, filtering, etc., and the optimization of the features for proper classification. In this article, DWT-based pre-processing and ABC is used for optimization of features which helps to achieve better classification accuracy. It is utilized for initial diagnosis of abnormalities. The signals are taken from MIT-BIH arrhythmia database for the analysis. The aim of the research is to classification of six diseases; Normal, Atrial, Paced, PVC, LBBB, RBBB with an ABC optimization algorithm and an ANN classification algorithm on the basis of the extracted features. Various parameters, like, FAR, FRR, and accuracy are measured for the execution. Comparative analysis is shown of the proposed and the existing work to depict the effectiveness of the work.

Download Full-text

Atrial Fibrillation in Dengue Infection: A Self-limiting Phenomenon? (Two Case Reports)

ACI (Acta Cardiologia Indonesiana) ◽

10.22146/aci.36637 ◽

2018 ◽

Vol 4 (1) ◽

pp. 36

Author(s):

Raymond Pranata ◽

Wendy Wiharja ◽

Vito Damay

Keyword(s):

Atrial Fibrillation ◽

Dengue Virus ◽

Case Reports ◽

Dengue Infection ◽

The Other ◽

Intravenous Fluids ◽

Close Monitoring ◽

Ns1 Antigen ◽

Ventricular Response ◽

Electrocardiogram Ecg

Dengue fever (DF) is highly prevalent in Indonesia as evidenced by 129,650 cases in 2015.Atrial fibrillation (AF) in dengue is exceptionally rare and usually self-limiting with resolution after recovery of illness. The aim of this case report is to depict two patients with AF in DF which resolves spontaneously in one and persists after infection in the other. Case 1 was 50 years old male presented with fever since 4 days before admission. NS1 antigen and IgM anti-Dengue virus were positive. An electrocardiogram (ECG) showed AF with rapid ventricular response (AFRVR). Case 2 was 53 years old male presented with dyspnea and palpitations 1 hour before admission. Patient had fever since 5 days before admission. Laboratory exams showed leukopenia, thrombocytopenia and positive IgM anti-Dengue virus. An electrocardiogram showed AFRVR. Intravenous fluids (normal saline), paracetamol, and digoxin were administered in both patients. They were admitted for close monitoring. Pre-discharge ECG of Case 1 showed resolution of AF. However, in Case 2, AF persists in pre-discharge ECG. In conclusion, physicians should be aware that a potentially reversible atrial fibrillation might be caused by this infection. It should be ensured that in those persisting cases, they should not be dismissed as just an ‘irreversible’ AF and progress into full-blown heart failure.

Download Full-text

An Automatic System for Atrial Fibrillation by Using a CNN-LSTM Model

Discrete Dynamics in Nature and Society ◽

10.1155/2020/3198783 ◽

2020 ◽

Vol 2020 ◽

pp. 1-9

Author(s):

Fengying Ma ◽

Jingyao Zhang ◽

Wei Chen ◽

Wei Liang ◽

Wenjia Yang

Keyword(s):

Atrial Fibrillation ◽

Classification Accuracy ◽

Short Term Memory ◽

Sequence Data ◽

Detection System ◽

Heart Rhythm ◽

Classification Performance ◽

Ecg Signals ◽

Electrocardiogram Ecg

Atrial fibrillation (AF) is a common abnormal heart rhythm disease. Therefore, the development of an AF detection system is of great significance to detect critical illnesses. In this paper, we proposed an automatic recognition method named CNN-LSTM to automatically detect the AF heartbeats based on deep learning. The model combines convolutional neural networks (CNN) to extract local correlation features and uses long short-term memory networks (LSTM) to capture the front-to-back dependencies of electrocardiogram (ECG) sequence data. The CNN-LSTM is feeded by processed data to automatically detect AF signals. Our study uses the MIT-BIH Atrial Fibrillation Database to verify the validity of the model. We achieved a high classification accuracy for the heartbeat data of the test set, with an overall classification accuracy rate of 97.21%, sensitivity of 97.34%, and specificity of 97.08%. The experimental results show that our model can robustly detect the onset of AF through ECG signals and achieve stable classification performance, thereby providing a suitable candidate for the automatic classification of AF.

Download Full-text

Disease Classification Using ECG Signals Based on R-Peak Analysis With ABC and ANN

10.4018/978-1-6684-2408-7.ch043 ◽

2022 ◽

pp. 933-954

Author(s):

Suman Lata ◽

Rakesh Kumar

Keyword(s):

Feature Extraction ◽

Comparative Analysis ◽

Classification Accuracy ◽

Disease Classification ◽

Cardiac Diseases ◽

Ecg Signals ◽

Processing Steps ◽

Ann Classification ◽

Selection Of

Download Full-text

Genotype impact on the economy of production performance in pigs

Agricultural Economics (Zemědělská ekonomika) ◽

10.17221/5085-agricecon ◽

2012 ◽

Vol 51 (No. 3) ◽

pp. 123-133 ◽

Cited By ~ 1

Author(s):

M. Šprysl ◽

R. Stupka ◽

J. Čítek

Keyword(s):

Production Performance ◽

The Other ◽

Quantitative Aspect ◽

Production Traits ◽

Fattening Performance ◽

Current Period ◽

Slaughter Pigs ◽

Significant Measure ◽

Selection Of

The test focussed on the evaluation of production traits, i.e. fattening performance and quantitative aspect of the carcass value in 4 genotypes of pigs by means of station tests. The tests included 288 hybrid pigs of the VEPIG and (LWd ×L) genotypes mated by hybrid-boars of (PN×D), (PN×H), (LWs×BL). The outcomes have proved the existence of marked genotype differences in the production traits and, consequently, also in the economics which means for the pig breeders in the current period a significant measure conducing to the improvement of the economics of pig breeding. As the best, there has been proved the VEPIG genotype of pigs, which has shown the best results in all qualities of the fattening performance and carcass value. This genotype has also reflected best its highest growth intensity in the formation of meat which has been manifested positively in the classification of slaughter pigs, i.e. the profit per a slaughter pig in the amount of 625 CZK. In contrast, the other combinations have shown a loss which in the (LWd×L) × (LWs×BL) genotypes amounted to 324.50 CZK, in (LWd×L) × (PN×D) 228 CZK and in  (LWd×L) × (PN×H) 279 CZK. Therefore it has to be stated that a deliberate selection of a suitable genotype is of a vital importance in order to be able to face the current considerably unfavourable situation in pig breeding.

Download Full-text

Interpretation of ECG recordings: part 2

HIGHER SCHOOL’S PULSE ◽

10.5604/01.3001.0014.8984 ◽

2021 ◽

Vol 15 (1) ◽

pp. 1-10

Author(s):

Michał Szurgot ◽

Weronika Wieczorek ◽

Beniamin Oskar Grabarek

Keyword(s):

Atrial Fibrillation ◽

Chronic Conditions ◽

Heart Defects ◽

P Wave ◽

Test Evaluation ◽

Key Factors ◽

Conduction Disorders ◽

Electrocardiogram Ecg ◽

The Waves ◽

Ecg Interpretation

The analysis of irregularities in an electrocardiogram (ECG) recording is one of the basic skills of every doctor. That is why becoming familiar with the principles of appropriate ECG interpretation is critical during training and should be mastered at the initial stages of education. An accurate and timely ECG analysis constitutes one of the key factors that determine the prognosis for a patient. At the first stage of test evaluation, irregularities in the components of an ECG must be analyzed, including the waves and segments on the printout. During evaluation, it must be considered that, under certain conditions, particular irregularities may not be apparent. For example, with atrial fibrillation, P wave deviations in the recording are sometimes not visible. The data contained in the ECG recording provides information about heart defects, conduction disorders in the heart muscle, hypothermia, and acute (e.g., myocardial infarction) or chronic conditions (e.g., atrial fibrillation, stable ischemic heart disease). It is important to interpret ECG results in conjunction with the patient’s condition and medical history.

Download Full-text

An Interpretable Hand-Crafted Feature-Based Model for Atrial Fibrillation Detection

Frontiers in Physiology ◽

10.3389/fphys.2021.657304 ◽

2021 ◽

Vol 12 ◽

Author(s):

Rahimeh Rouhi ◽

Marianne Clausel ◽

Julien Oster ◽

Fabien Lauer

Keyword(s):

Atrial Fibrillation ◽

Heart Rhythm ◽

Point Of View ◽

Compact Set ◽

Ecg Signals ◽

Feature Based ◽

Electrocardiogram Ecg ◽

The Impact ◽

Aided Diagnosis

Atrial Fibrillation (AF) is the most common type of cardiac arrhythmia. Early diagnosis of AF helps to improve therapy and prognosis. Machine Learning (ML) has been successfully applied to improve the effectiveness of Computer-Aided Diagnosis (CADx) systems for AF detection. Presenting an explanation for the decision made by an ML model is considerable from the cardiologists' point of view, which decreases the complexity of the ML model and can provide tangible information in their diagnosis. In this paper, a range of explanation techniques is applied to hand-crafted features based ML models for heart rhythm classification. We validate the impact of the techniques by applying feature selection and classification to the 2017 CinC/PhysioNet challenge dataset. The results show the effectiveness and efficiency of SHapley Additive exPlanations (SHAP) technique along with Random Forest (RF) for the classification of the Electrocardiogram (ECG) signals for AF detection with a mean F-score of 0.746 compared to 0.706 for a technique based on the same features based on a cascaded SVM approach. The study also highlights how this interpretable hand-crafted feature-based model can provide cardiologists with a more compact set of features and tangible information in their diagnosis.

Download Full-text

Loop Based Design and Classification of Planar Scissor Linkages

10.21203/rs.3.rs-23111/v1 ◽

2020 ◽

Author(s):

Gökhan Kiper ◽

Koray Korkmaz ◽

Şebnem Gür ◽

Müjde ◽

Feray Maden ◽

...

Keyword(s):

The Other ◽

Systematic Classification ◽

Related Literature ◽

Selection Of

Abstract Scissor linkages have been used for several applications since ancient Greeks and Romans. In addition to simple scissor linkages with straight rods, linkages with angulated elements were introduced in the last decades. In the related literature, two methods seem to be used to design scissor linkages, one of which is based on scissor elements, and the other is based on assembling loops. This study presents a systematic classification of scissor linkages as assemblies of rhombus, kite, dart, parallelogram and anti-parallelogram loops using frieze patterns and long-short diagonal connections. After the loops are multiplied along a curve as a pattern, the linkages are obtained by selection of proper common link sections for adjacent loops. The resulting linkages are analyzed for their motion and they are classified as realizing scaling deployable, angular deployable or transformable motion. Some of the linkages obtained are novel. Totally 10 scalable deployable, 1 angular deployable and 8 transformable scissor linkages are listed. Designers in architecture and engineering can use this list of linkages as a library of scissor linkage topologies.

Download Full-text

Note on Selection of Coordinate Systems for Geodynamics

International Astronomical Union Colloquium ◽

10.1017/s0252921100051174 ◽

1975 ◽

Vol 26 ◽

pp. 395-407

Author(s):

S. Henriksen

Keyword(s):

Sea Level ◽

The Other ◽

Coordinate Systems ◽

Mean Sea Level ◽

The Earth ◽

The One ◽

Static Systems ◽

Selection Of

The first question to be answered, in seeking coordinate systems for geodynamics, is: what is geodynamics? The answer is, of course, that geodynamics is that part of geophysics which is concerned with movements of the Earth, as opposed to geostatics which is the physics of the stationary Earth. But as far as we know, there is no stationary Earth – epur sic monere. So geodynamics is actually coextensive with geophysics, and coordinate systems suitable for the one should be suitable for the other. At the present time, there are not many coordinate systems, if any, that can be identified with a static Earth. Certainly the only coordinate of aeronomic (atmospheric) interest is the height, and this is usually either as geodynamic height or as pressure. In oceanology, the most important coordinate is depth, and this, like heights in the atmosphere, is expressed as metric depth from mean sea level, as geodynamic depth, or as pressure. Only for the earth do we find “static” systems in use, ana even here there is real question as to whether the systems are dynamic or static. So it would seem that our answer to the question, of what kind, of coordinate systems are we seeking, must be that we are looking for the same systems as are used in geophysics, and these systems are dynamic in nature already – that is, their definition involvestime.

Download Full-text