Search results for: mechanical heart valve

Authors: Frazer Kirk, Matthew Yong, Peter Williams, Andrie Strobel

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Pulmonary valve papillary fibroelastoma is an exceedingly rare pathology. The experience and literature regarding them are largely anecdotal and based on sporadic, single case reports. Throughout their known history, two features remain salient that they are classically asymptomatic and found incidentally. The demographic profile of those affected is unclear, as reports regarding those affected are mixed, and there is no clear gender or age predominance, although there is some suggestion of a predisposition to affect females. Nor has there been a well-structured epidemiological study of the entity. Interestingly they are becoming more common on peri-mortum examination. Here-after we describe our experience with a symptomatic presentation of pulmonary papillary fibroelastoma masquerading as a pulmonary embolism and its subsequent assessment and management, with intraoperative photography and echocardiography for reference.

Keywords: cardiac tumor, pulmonary valve, fibroelastoma, cardiac surgery

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Authors: Hyo Lim Kang, Tae An Kim, Seung Ho Han

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A 3-way reversing valve has been used in automotive washing machines to remove remaining oil and dirt on machined engine and transmission blocks. It provides rapid and accurate changes of water flow direction without any precise control device. However, due to its complicated bottom-plug shape, a cavitation occurs in a wide range of the bottom-plug in a downstream. In this study, the cavitation index and POC (percent of cavitation) were used to evaluate quantitatively the cavitation phenomena occurring at the bottom-plug. An optimal shape design was carried out via parametric study for geometries of the bottom-plug, in which a simple CAE-model was used in order to avoid time-consuming CFD analysis and hard to achieve convergence. To verify the results of numerical analysis, a flow visualization test was carried out using a test specimen with a transparent acryl pipe according to ISA-RP75.23. The flow characteristics such as the cavitation occurring in the downstream were investigated by using a flow test equipment with valve and pump including a flow control system and high-speed camera.

Keywords: cavitation, flow visualization test, optimal shape design, percent of cavitation, reversing valve

Procedia PDF Downloads 271

Authors: Mazhar B. Tayel, Eslam I. AlSaba

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The heart is the most important part in any body organisms. It effects and affected by any factor in the body. Therefore, it is a good detector of any matter in the body. When the heart signal is non-stationary signal, therefore, it should be study its variability. So, the Heart Rate Variability (HRV) has attracted considerable attention in psychology, medicine and have become important dependent measure in psychophysiology and behavioral medicine. Quantification and interpretation of heart rate variability. However, remain complex issues are fraught with pitfalls. This paper presents one of the non-linear techniques to analyze HRV. It discusses 'What Poincare plot is?', 'How it is work?', 'its usage benefits especially in HRV', 'the limitation of Poincare cause of standard deviation SD1, SD2', and 'How overcome this limitation by using complex correlation measure (CCM)'. The CCM is most sensitive to changes in temporal structure of the Poincaré plot as compared to SD1 and SD2.

Keywords: heart rate variability, chaotic system, poincare, variance, standard deviation, complex correlation measure

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Authors: Nazanin Ahmadi Daryakenari

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Background: Diabetes significantly influences the risk of heart failure. The interplay between distinct types of diabetes, heart failure, and their distribution across various age groups remains an area of active exploration. This study endeavors to scrutinize the age group distribution in publications addressing Type 1 and Type 2 diabetes and heart failure on PubMed while also examining the evolving publication trends. Methods: We leveraged E-utilities and RegEx to search and extract publication data from PubMed using various mesh terms. Subsequently, we conducted descriptive statistics and t-tests to discern the differences between the two diabetes types and the distribution across age groups. Finally, we analyzed the temporal trends of publications concerning both types of diabetes and heart failure. Results: Our findings revealed a divergence in the age group distribution between Type 1 and Type 2 diabetes within heart failure publications. Publications discussing Type 2 diabetes and heart failure were more predominant among older age groups, whereas those addressing Type 1 diabetes and heart failure displayed a more balanced distribution across all age groups. The t-test revealed no significant difference in the means between the two diabetes types. However, the number of publications exploring the relationship between Type 2 diabetes and heart failure has seen a steady increase over time, suggesting an escalating interest in this area. Conclusion: The dissection of publication patterns on PubMed uncovers a pronounced association between Type 2 diabetes and heart failure within older age groups. This highlights the critical need to comprehend the distinct age group differences when examining diabetes and heart failure to inform and refine targeted prevention and treatment strategies.

Keywords: Type 1 diabetes, Type 2 diabetes, heart failure, age groups, publication patterns, PubMed

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Authors: Ahmed Bensreti, Mohamed Gouarsha

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This paper presents a review of the pressure surge simulations carried out for Phase III of the Man Made River project in Libya with particular emphasis on the transient generated by simultaneous pump trips at Al Gardabiya Pump Station. The omission of the surge vessel check valve and bypass system on the grounds of cost, ease of design, and construction will result in, as expected, increased surge fluctuations as the damping effect in the form was removed. From the hydraulic and control requirements, it is recommended for Al Gardabiya Pump station that the check valve and check valve bypass be included in the final surge vessel design.

Keywords: computational fluid dynamics, surge vessel design, transient surge analysis, water pipe hydraulics

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Authors: Suzan Anwar, Utkarsh Goyal

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Heart rate (HR) is a predictor of cardiovascular, cerebrovascular, and all-cause mortality in the general population, as well as in patients with cardio and cerebrovascular diseases. Machine learning (ML) significantly improves the accuracy of cardiovascular risk prediction, increasing the number of patients identified who could benefit from preventive treatment while avoiding unnecessary treatment of others. This research examines relationship between the individual's various heart health inputs like age, sex, cp, trestbps, thalach, oldpeaketc, and the likelihood of developing heart disease. Machine learning techniques like logistic regression and decision tree, and Python are used. The results of testing and evaluating the model using the Heart Failure Prediction Dataset show the chance of a person having a heart disease with variable accuracy. Logistic regression has yielded an accuracy of 80.48% without data handling. With data handling (normalization, standardscaler), the logistic regression resulted in improved accuracy of 87.80%, decision tree 100%, random forest 100%, and SVM 100%.

Keywords: heart rate, machine learning, SVM, decision tree, logistic regression, random forest

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Authors: Nur Azzammudin Rahmat, Ismail Musirin, Ahmad Farid Abidin

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Economic load dispatch is performed by the utilities in order to determine the best generation level at the most feasible operating cost. In order to guarantee satisfying energy delivery to the consumer, a precise calculation of generation level is required. In order to achieve accurate and practical solution, several considerations such as prohibited operating zones, valve-point effect and ramp-rate limit need to be taken into account. However, these considerations cause the optimization to become complex and difficult to solve. This research focuses on the valve-point effect that causes ripple in the fuel-cost curve. This paper also proposes Differential Evolution Immunized Ant Colony Optimization (DEIANT) in solving economic load dispatch problem with valve-point effect. Comparative studies involving DEIANT, EP and ACO are conducted on IEEE 30-Bus RTS for performance assessments. Results indicate that DEIANT is superior to the other compared methods in terms of calculating lower operating cost and power loss.

Keywords: ant colony optimization (ACO), differential evolution (DE), differential evolution immunized ant colony optimization (DEIANT), economic load dispatch (ELD)

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Authors: Sara R. Knigge, Sugat R. Tuladhar, Hans-Klaus HöFfler, Tobias Schilling, Tim Kaufeld, Axel Haverich

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Tissue engineered (TE) heart valves based on degradable electrospun fiber scaffold represent a promising approach to overcome the known limitations of mechanical or biological prostheses. But the mechanical stress in the high-pressure system of the human circulation is a severe challenge for the delicate materials. Hence, the prediction of the scaffolds` in vivo degradation kinetics must be as accurate as possible to prevent fatal events in future animal or even clinical trials. Therefore, this study investigates whether long-term testing in full blood provides more meaningful results regarding the degradation behavior than conventional tests in simulated body fluids (SBF) or Phosphate Buffered Saline (PBS). Fiber mats were produced from a polycaprolactone (PCL)/tetrafluoroethylene solution by electrospinning. The morphology of the fiber mats was characterized via scanning electron microscopy (SEM). A maximum physiological degradation environment utilizing a test set-up with porcine full blood was established. The set-up consists of a reaction vessel, an oxygenator unit, and a roller pump. The blood parameters (pO2, pCO2, temperature, and pH) were monitored with an online test system. All tests were also carried out in the test circuit with SBF and PBS to compare conventional degradation media with the novel full blood setting. The polymer's degradation is quantified by SEM picture analysis, differential scanning calorimetry (DSC), and Raman spectroscopy. Tensile and cyclic loading tests were performed to evaluate the mechanical integrity of the scaffold. Preliminary results indicate that PCL degraded slower in full blood than in SBF and PBS. The uptake of water is more pronounced in the full blood group. Also, PCL preserved its mechanical integrity longer when degraded in full blood. Protein absorption increased during the degradation process. Red blood cells, platelets, and their aggregates adhered on the PCL. Presumably, the degradation led to a more hydrophilic polymeric surface which promoted the protein adsorption and the blood cell adhesion. Testing degradable implants in full blood allows for developing more reliable scaffold materials in the future. Material tests in small and large animal trials thereby can be focused on testing candidates that have proven to function well in an in-vivo-like setting.

Keywords: Electrospun scaffold, full blood degradation test, long-term polymer degradation, tissue engineered aortic heart valve

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Authors: Jia Xin Low, Keng Wah Choo

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This paper presents an automatic normal and abnormal heart sound classification model developed based on deep learning algorithm. MITHSDB heart sounds datasets obtained from the 2016 PhysioNet/Computing in Cardiology Challenge database were used in this research with the assumption that the electrocardiograms (ECG) were recorded simultaneously with the heart sounds (phonocardiogram, PCG). The PCG time series are segmented per heart beat, and each sub-segment is converted to form a square intensity matrix, and classified using convolutional neural network (CNN) models. This approach removes the need to provide classification features for the supervised machine learning algorithm. Instead, the features are determined automatically through training, from the time series provided. The result proves that the prediction model is able to provide reasonable and comparable classification accuracy despite simple implementation. This approach can be used for real-time classification of heart sounds in Internet of Medical Things (IoMT), e.g. remote monitoring applications of PCG signal.

Keywords: convolutional neural network, discrete wavelet transform, deep learning, heart sound classification

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Authors: Sarakorn Sukaviriya

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This paper describes the inspection procedure, root cause analysis, the rectification of crack, and how to apply the procedure with other similar plants. During the operation of the steam turbine (620MW), instruments such as speed sensor of steam turbine, the servo valve of main stop valve and electrical wires were malfunction caused by leakage steam from main steam governing valve. Therefore, the power plant decided to shutdown steam turbines for figuring out the cause of leakage steam. Inspection techniques to be applied in this problem were microstructure testing (SEM), pipe stress analysis (FEM) and non-destructive testing. The crack was initially found on main governing valve’s weldment by visual inspection. To analyze more precisely, pipe stress analysis and microstructure testing were applied and results indicated that the crack was intergranular and originated from the weld defect. This weld defect caused the notch with high-stress concentration which created crack and then propagated to steam leakage. The major root cause of this problem was an inappropriate welding process, which created a weld defect. To repair this joint from damage, we used a welding technique by producing refinement of coarse grain HAZ and eliminating stress concentration. After the weldment was completely repaired, other adjacent weldments still had risk. Hence, to prevent any future cracks, non-destructive testing (NDT) shall be applied to all joints in order to ensure that there will be no indication of crack.

Keywords: steam-pipe leakage, steam leakage, weld crack analysis, weld defect

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Authors: Lucia Carrion Gordon, Jaime Santiago Sanchez Reinoso

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According to the relation of Digital Preservation and the Health field as a case of study, the architectural model help us to explain that definitions. .The principal goal of Data Preservation is to keep information for a long term. Regarding of Mediacal information, in order to perform a heart transplant, physicians need to preserve this organ in an adequate way. This approach between the two perspectives, the medical and the technological allow checking the similarities about the concepts of preservation. Digital preservation and medical advances are related in the same level as knowledge improvement.

Keywords: medical management, digital, data, heritage, preservation

Procedia PDF Downloads 388

Authors: Estelle Démoulin, Dionysios Adamopoulos, Tornike Sologashvili, Mathieu Van Steenberghe, Jalal Jolou, Haran Burri, Christoph Huber, Mustafa Cikirikcioglu

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Background & objective: Mitral valve surgeries are mainly performed by median sternotomy with conventional direct atriotomy. Good exposure to the mitral valve is challenging, especially for acute pathologies, where left atrium dilation does not occur. Other atriotomies, such as transseptal or superior septal, are used as they allow better access and visualization. Peri- and postoperative outcomes of these three different left atriotomies were compared. Methods: Patients undergoing mitral valve surgery between January 2010 and December 2020 were included and divided into three groups: group 1 (conventional direct, n=115), group 2 (transseptal, n=33) and group 3 (superior septal, n=59). To improve the sampling size, all patients underwent mitral valve surgery with or without associated procedures (CABG, aortic-tricuspid surgery, Maze procedure). The study protocol was approved by SwissEthics. Results: No difference was shown for the etiology of mitral valve disease, except endocarditis, which was more frequent in group 3 (p = 0.014). Elective surgeries and isolated mitral valve surgery were more frequent in group 1 (p = 0.008, p = 0.011) and aortic clamping and cardiopulmonary bypass were shorter (p = 0.002, p<0.001). Group 3 had more emergency procedures (p = 0.011) and longer lengths of intensive care unit and hospital stay (p = 0.000, p = 0.003). There was no difference in permanent pacemaker implantation, postoperative complications and mortality between the groups. Conclusion: Mitral valve surgeries can be safely performed using those three left atriotomies. Conventional direct may lead to shorter aortic clamping and cardiopulmonary bypass times. Superior septal is mostly used for acute pathologies, and it does not increase postoperative arrhythmias and permanent pacemaker implantation. However, intensive care unit and hospital lengths of stay were found to be longer in this group. In our opinion, this outcome is more related to the pathology and type of surgery than the incision itself.

Keywords: Mitral valve surgery, cardiac surgery, atriotomy, Operative outcomes

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Authors: Ramanen Sugunesegran, Michael L. Williams

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Over the past two decades surgical approaches for mitral valve (MV) disease have evolved with the advent of minimally invasive techniques. Robotic mitral valve repair (RMVr) safety and efficacy has been well documented, however, mid- to long-term data are limited. The aim of this review was to provide a comprehensive analysis of the available mid- to long-term term data for RMVr. Electronic searches of five databases were performed to identify all relevant studies reporting minimum 5-year data on RMVr. Pre-defined primary outcomes of interest were overall survival, freedom from MV reoperation and freedom from moderate or worse mitral regurgitation (MR) at 5-years or more post-RMVr. A meta-analysis of proportions or means was performed, utilizing a random effects model, to present the data. Kaplan-Meier curves were aggregated using reconstructed individual patient data. Nine studies totaling 3,300 patients undergoing RMVr were identified. Rates of overall survival at 1-, 5- and 10-years were 99.2%, 97.4% and 92.3%, respectively. Freedom from MV reoperation at 8-years post RMVr was 95.0%. Freedom from moderate or worse MR at 7-years was 86.0%. Rates of early post-operative complications were low with only 0.2% all-cause mortality and 1.0% cerebrovascular accident. Reoperation for bleeding was low at 2.2% and successful RMVr was 99.8%. Mean intensive care unit and hospital stay were 22.4 hours and 5.2 days, respectively. RMVr is a safe procedure with low rates of early mortality and other complications. It can be performed with low complication rates in high volume, experienced centers. Evaluation of available mid-term data post-RMVr suggests favorable rates of overall survival, freedom from MV reoperation and freedom from moderate or worse MR recurrence.

Keywords: mitral valve disease, mitral valve repair, robotic cardiac surgery, robotic mitral valve repair

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Authors: Onder Yakut, Oguzhan Timus, Emine Dogru Bolat

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Health diseases have a vital significance affecting human being's life and life quality. Sudden death events can be prevented owing to early diagnosis and treatment methods. Electrical signals, taken from the human being's body using non-invasive methods and showing the heart activity is called Electrocardiogram (ECG). The ECG signal is used for following daily activity of the heart by clinicians. Heart Rate Variability (HRV) is a physiological parameter giving the variation between the heart beats. ECG data taken from MITBIH Arrhythmia Database is used in the model employed in this study. The detection of arrhythmic heart beats is aimed utilizing the features extracted from the HRV time domain parameters. The developed model provides a satisfactory performance with ~89% accuracy, 91.7 % sensitivity and 85% specificity rates for the detection of arrhythmic beats.

Keywords: arrhythmic beat detection, ECG, HRV, kNN classifier

Procedia PDF Downloads 317

Authors: Rossana Taravella, Gilberto M. Cellura, Giuseppe Cirrincione, Salvatore Asciutto, Marco Caruso, Massimo Benedetto, Renato Ciofalo, Giuliana Pace, Salvatore Novo

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Objectives: This retrospective analysis sought to evaluate 1-month outcomes and therapy effectiveness of a population of patients treated with MitraClip therapy. We describe in this article the preliminary results of primary effectiveness endpoint. Background: Percutaneous Mitral Repair is being developed to treat severe mitral regurgitation (MR), with increasing real-world cases of functional MR (FMR). In the EVEREST (Endovascular Valve Edge-to-Edge Repair Study)II trial, the percutaneous device showed superior safety but less reduction in MR at 1year. 4-year outcomes from EVEREST II trial showed no difference in the prevalence of moderate-severe and severe MR or mortality at 4years between surgical mitral repair and percutaneous approach. Methods: We analysed retrospectively collected data from one center experience in Italy enrolled from January 2011 to December 2016. The study included 62 patients [mean age 74±11years, 43 men (69%)] with MR of at least grade3+. Most of the patients had functional MR, were in New York Heart Association (NYHA) functional class III or IV, with a large portion (78%) of mild-to-moderate Tricuspid Regurgitation (TR). One or more clips were implanted in 67 procedures (62 patients). Results and Conclusions: Severity of MR was reduced in all successfully treated patients,54(90%) were discharged with MR≤2+ (primary effectiveness endpoint). Clinical 1-month follow-up data showed an improvement in NYHA functional class (42 patients (70%) in NYHA class I-II). 60 of 62 (97 %) successfully treated patients were free from death and mitral valve surgery at 1-month follow-up. MitraClip therapy reduces functional MR with acute MR reduction to <2+ in the great majority of patients, with a large freedom from death, surgery or recurrent MR in a great portion of patients.

Keywords: MitraClip, mitral regurgitation, heart valves, catheter-based therapy

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Authors: Kianoosh Ahadi, Mustafa Ergil

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In this study, the event of vibrations caused by vortexes and the distribution of induced hydrodynamic forces due to vortexes on the sliding gate valves has been investigated. For this reason, a sliding valve with the help of computational fluid dynamics (CFD) software was simulated in two-dimensional )2D(, where the flow and turbulence equations were solved for three different valve openings (full, half, and 16.7 %) models. The variety of vortexes formed within the vicinity of the valve structure was investigated based on time where the trend of fluctuations and their occurrence regions have been detected. From the gathered solution dataset of the numerical simulations, the pressure coefficient (CP), the lift force coefficient (CL), the drag force coefficient (CD), and the momentum coefficient due to hydrodynamic forces (CM) were examined, and relevant figures were generated were from these results, the vortex-induced vibrations were analyzed.

Keywords: induced vibrations, computational fluid dynamics, sliding gate valves, vortexes

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Authors: Yongrong Liu, Xin Tang

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Background: Persistent atrial fibrillation is a common arrhythmia closely related to heart failure. Heart rate control is an essential strategy for treating persistent atrial fibrillation. Still, the understanding of the relationship between different heart rate control levels and the risk of heart failure rehospitalization is limited. Objective: The objective of the study is to determine the relationship between different levels of heart rate control in patients with persistent atrial fibrillation and the risk of readmission for heart failure. Methods: We conducted a retrospective dual-centre cohort study, collecting data from patients with persistent atrial fibrillation who received outpatient treatment at two tertiary hospitals in central and western China from March 2019 to March 2020. The collected data included age, gender, body mass index (BMI), medical history, and hospitalization frequency due to heart failure. Patients were divided into three groups based on their heart rate control levels: Group I with a resting heart rate of less than 80 beats per minute, Group II with a resting heart rate between 80 and 100 beats per minute, and Group III with a resting heart rate greater than 100 beats per minute. The readmission rates due to heart failure within one year after discharge were statistically analyzed using propensity score matching in a 1:1 ratio. Differences in readmission rates among the different groups were compared using one-way ANOVA. The impact of varying levels of heart rate control on the risk of readmission for heart failure was assessed using the Cox proportional hazards model. Binary logistic regression analysis was employed to control for potential confounding factors. Results: We enrolled a total of 1136 patients with persistent atrial fibrillation. The results of the one-way ANOVA showed that there were differences in readmission rates among groups exposed to different levels of heart rate control. The readmission rates due to heart failure for each group were as follows: Group I (n=432): 31 (7.17%); Group II (n=387): 11.11%; Group III (n=317): 90 (28.50%) (F=54.3, P<0.001). After performing 1:1 propensity score matching for the different groups, 223 pairs were obtained. Analysis using the Cox proportional hazards model showed that compared to Group I, the risk of readmission for Group II was 1.372 (95% CI: 1.125-1.682, P<0.001), and for Group III was 2.053 (95% CI: 1.006-5.437, P<0.001). Furthermore, binary logistic regression analysis, including variables such as digoxin, hypertension, smoking, coronary heart disease, and chronic obstructive pulmonary disease as independent variables, revealed that coronary heart disease and COPD also had a significant impact on readmission due to heart failure (p<0.001). Conclusion: The correlation between the heart rate control level of patients with persistent atrial fibrillation and the risk of heart failure rehospitalization is positive. Reasonable heart rate control may significantly reduce the risk of heart failure rehospitalization.

Keywords: heart rate control levels, heart failure rehospitalization, persistent atrial fibrillation, retrospective cohort study

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Authors: Chiang-Ho Cheng, An-Shik Yang, Chih-Jer Lin, Chun-Ying Lee

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This paper aims to present the design, fabrication and test of a novel piezoelectric actuated, check-valves embedded micropump having the advantages of miniature size, light weight and low power consumption. This device is designed to pump gases and liquids with the capability of performing the self-priming and bubble-tolerant work mode by maximizing the stroke volume of the membrane as well as the compression ratio via minimization of the dead volume of the micropump chamber and channel. By experiment apparatus setup, we can get the real-time values of the flow rate of micropump, the displacement of the piezoelectric actuator and the deformation of the check valve, simultaneously. The micropump with check valve 0.4 mm in thickness obtained higher output performance under the sinusoidal waveform of 120 Vpp. The micropump achieved the maximum pumping rates of 42.2 ml/min and back pressure of 14.0 kPa at the corresponding frequency of 28 and 20 Hz. The presented micropump is able to pump gases with a pumping rate of 196 ml/min at operating frequencies of 280 Hz under the sinusoidal waveform of 120 Vpp.

Keywords: actuator, check-valve, micropump, piezoelectric

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Authors: Oluwaponmile David Alao

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Due to an increase in the death rate as a result of heart attack. There is need to develop a system that can be useful in the diagnosis of the disease at the medical centre. This system will help in preventing misdiagnosis that may occur from the medical practitioner or the physicians. In this research work, heart disease dataset obtained from UCI repository has been used to develop an intelligent prediction diagnosis system. The system is modeled on a feedforwad neural network and trained with back propagation neural network. A recognition rate of 86% is obtained from the testing of the network.

Keywords: heart disease, artificial neural network, diagnosis, prediction system

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Authors: Yang Zhang, Jian He

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Heart disease is one of the leading causes of death in the world, and coronary heart disease (CHD) is one of the major heart diseases. Electrocardiogram (ECG) is widely used in the detection of heart diseases, but the traditional manual method for CHD prediction by analyzing ECG requires lots of professional knowledge for doctors. This paper introduces sliding window and continuous wavelet transform (CWT) to transform ECG signals into images, and then ResNet and Bi-LSTM are introduced to build the ECG feature extraction network (namely ECGNet). At last, an auxiliary system for coronary heart disease prediction was developed based on modified ResNet18 and Bi-LSTM, and the public ECG dataset of CHD from MIMIC-3 was used to train and test the system. The experimental results show that the accuracy of the method is 83%, and the F1-score is 83%. Compared with the available methods for CHD prediction based on ECG, such as kNN, decision tree, VGGNet, etc., this method not only improves the prediction accuracy but also could avoid the degradation phenomenon of the deep learning network.

Keywords: Bi-LSTM, CHD, ECG, ResNet, sliding window

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Authors: Santanu Chattopadhyay, Gautam Sarkar, Arabinda Das

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This paper presents wavelet based classification of various heart diseases. Electrocardiogram signals of different heart patients have been studied. Statistical natures of electrocardiogram signals for different heart diseases have been compared with the statistical nature of electrocardiograms for normal persons. Under this study four different heart diseases have been considered as follows: Myocardial Ischemia (MI), Congestive Heart Failure (CHF), Arrhythmia and Sleep Apnea. Statistical nature of electrocardiograms for each case has been considered in terms of kurtosis values of two types of wavelet coefficients: approximate and detail. Nine wavelet decomposition levels have been considered in each case. Kurtosis corresponding to both approximate and detail coefficients has been considered for decomposition level one to decomposition level nine. Based on significant difference, few decomposition levels have been chosen and then used for classification.

Keywords: arrhythmia, congestive heart failure, discrete wavelet transform, electrocardiogram, myocardial ischemia, sleep apnea

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Authors: Goran Begović

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In recent years, many researchers are focusing on non-intrusive measuring methods when it comes to human biosignals. These methods provide solutions for everyday use, whether it’s health monitoring or finessing the workout routine. One of the biggest issues with these solutions is that the sensors’ accuracy is highly variable due to many factors, such as ambiental light, skin color diversity, etc. That is why we wanted to explore different outcomes under those kinds of circumstances in order to find the most optimal algorithm(s) for extracting heart rate (HR) information. The optimization of such algorithms can benefit the wider, cheaper, and safer application of home health monitoring, without having to visit medical professionals as often when it comes to observing heart irregularities. In this study, we explored the accuracy of infrared (IR), red, and green LED sensorics in a controlled environment and compared the results with a medically accurate ECG monitoring device.

Keywords: data science, ECG, heart rate, holter monitor, LED sensors

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Authors: Madeleine Nicole G. Bernardo, Katrina T. Feliciano, Marcelo Nonato A. Nacionales III, Diane Frances M. Peralta, Denise Nicole V. Profeta

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This study aims to find out if heart rate variability and valence of emotion have an effect on perceived intensity of emotion. Psychology undergraduates (N = 60) from the University of the Philippines Diliman were shown 10 photographs from the Japanese Female Facial Expression (JAFFE) Database, along with a corresponding questionnaire with a Likert scale on perceived intensity of emotion. In this 3 x 2 mixed subjects factorial design, each group was either made to do a simple exercise prior to answering the questionnaire in order to increase the heart rate, listen to a heart rate of 120 bpm, or colour a drawing to keep the heart rate stable. After doing the activity, the participants then answered the questionnaire, providing a rating of the faces according to the participants’ perceived emotional intensity on the photographs. The photographs presented were either of positive or negative emotional valence. The results of the experiment showed that neither an induced fast heart rate or perceived fast heart rate had any significant effect on the participants’ perceived intensity of emotion. There was also no interaction effect of heart rate variability and valence of emotion. The insignificance of results was explained by the Philippines’ high context culture, accompanied by the prevalence of both intensely valenced positive and negative emotions in Philippine society. Insignificance in the effects were also attributed to the Cannon-Bard theory, Schachter-Singer theory and various methodological limitations.

Keywords: heart rate variability, perceived intensity of emotion, Philippines , valence of emotion

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Authors: P. Halder, A. Zaman

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It is estimated that heart disease accounts for one in ten deaths worldwide. United States deaths due to heart disease are among the leading causes of death according to the World Health Organization. Cardiovascular diseases (CVDs) account for one in four U.S. deaths, according to the Centers for Disease Control and Prevention (CDC). According to statistics, women are more likely than men to die from heart disease as a result of strokes. A 50% increase in men's mortality was reported by the World Health Organization in 2009. The consequences of cardiovascular disease are severe. The causes of heart disease include diabetes, high blood pressure, high cholesterol, abnormal pulse rates, etc. Machine learning (ML) can be used to make predictions and decisions in the healthcare industry. Thus, scientists have turned to modern technologies like Machine Learning and Data Mining to predict diseases. The disease prediction is based on four algorithms. Compared to other boosts, the Ada boost is much more accurate.

Keywords: heart disease, cardiovascular disease, coronary artery disease, feature selection, random forest, AdaBoost, SVM, decision tree

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Authors: A. Kherraf, M. Bouziane, A. Drighil, L. Azzouzi, R. Habbal

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Objective: Myxomas are rare heart tumors most commonly found in the left atrium. The purpose of this observation is to report a rare case of myxoma of the right atrium revealed by pulmonary embolism. Observation: A 34-year-old patient with no history presented to the emergency room with sudden onset dyspnea. Clinical examination showed arterial pressure at 110/70mmHg, tachycardia at 110bpm, and 90% oxygen saturation. The ECG enrolled in incomplete right bundle branch block. The radio-thorax was normal. Echocardiography revealed the presence of a large homogeneous intra-OD mass, contiguous to the inter-atrial septum, prolapsing through the tricuspid valve, and causing mild tricuspid insufficiency, with dilation of the right ventricle and retained systolic function with PAPs estimated at 45mmHg. A chest scan was performed, revealing the presence of right segmental pulmonary embolism. The patient was put under anticoagulant and underwent surgical resection of the mass; its pathological examination concluded to a myxoma. The post-operative consequences were simple, without recurrence of the mass after one year follow-up. Discussion: Myxomas represent 50% of heart tumors. Most often, they originate in the left atrium, and more rarely in the right atrium or the ventricles. Myxoma of the right atrium can be responsible for life-threatening pulmonary embolism. The most predictive factor for embolization remains the morphology of the myxomas; papillary or villous myxomas are the most friable. Surgery is the standard treatment, with regular postoperative follow-up to detect recurrence. Conclusion: Myxomas of the right atrium are a rare location for these tumors. Pulmonary embolism is the main complication and should routinely involve careful study of the right chambers on echocardiography.

Keywords: pulmonary embolism, myxoma, right atrium, heart tumors

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Authors: G. Dadashova, A. Bakhshaliyev

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Aim: Determine gender differences in the etiology and clinical outcomes, as well as in the remodeling of the left ventricle (LV) in patients with chronic heart failure (CHF), suffering from arterial hypertension (AH) and coronary heart disease (CHD). Material and methods: The study included 112 patients of both sexes; aged 45 to 60 years with postinfarction cardiosclerosis had functional class (FC) heart failure II-IV of NYHA which were examined on the basis of Azerbaijan Scientific Research Institute of Cardiology. The patients were divided into 2 groups: 1st c. 60 males, mean age 54,8 ± 3,3 years, and 2nd gr 52 women, mean age 55,8 ± 3,1 years. To assess cardiac hemodynamic all patients underwent echocardiography (B-M-modes) using ‘Vivid 3’. Thus on the basis of indicators such as the index of the relative thickness of the left ventricle wall and the index of left ventricular mass (LVMI) was identified the architectonic model of the left ventricle. Results: According to our research leading cause of heart failure in women is 50.5% of cases of hypertension, ischemic heart disease 23.7% (with 79.5% of the cases developed in patients with chronic heart failure who did not have a history of myocardial infarction). While in men is the undisputed leader of CHD, forming 78.3% of CHF (80.3% in men with CHF occurred after myocardial infarction). According to our research in women more often than men CHF develops a type of diastolic dysfunction (DD, and left ventricular ejection fraction remained unchanged. Since DD occurs in men at 65,8% vs. 76,4% of women when p < 0,05. In the group of women was more common prognostic neblagopryatnye remodeling - eccentric hypertrophy of the left ventricle: 68% vs. 54.5% among men (p < 0,05), concentric left ventricular hypertrophy: 21% in women vs 19,1% (p > 0,05 ). Conclusions: Patients with heart failure are a number of gender-specific: the prevalence of hypertension in women, and coronary heart disease in men. While in women with heart failure often recorded diastolic dysfunction and characterized by the development of prognostically unfavorable remodeling types: eccentric and concentric LV hypertrophy.

Keywords: chronic heart failure, arterial hypertension, remodeling, diastolic dysfunction, men, women, ischemic heart disease

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Authors: Kaouther Selmi, Alaeddine Sridi, Mohamed Bouallegue, Kais Bouallegue

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Neurons are the fundamental units of the brain and the nervous system. The variable structure model of neurons consists of a system of differential equations with various parameters. By optimizing these parameters, we can create a unique model that describes the dynamic behavior of a single neuron. We introduce a neural network based on neurons with multiple dendrites employing an activation function with a variable structure. In this paper, we present a model for heart behavior. Finally, we showcase our successful simulation of the heart's ECG diagram using our Variable Structure Neuron Model (VSMN). This result could provide valuable insights into cardiology.

Keywords: neural networks, neuron, dendrites, heart behavior, ECG

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Authors: Linda Saili, Amel Hanini, Chiraz Smirani, Iness Azzouz, Amina Azzouz, Hafedh Abdemelek, Zihad Bouslama

Abstract:

Electrocardiogram and arterial pressure measurements were studied under acute exposures to WIFI (2.45 GHz) during one hour in adult male rabbits. Antennas of WIFI were placed at 25 cm at the right side near the heart. Acute exposure of rabbits to WIFI increased heart frequency (+ 22%) and arterial blood pressure (+14%). Moreover, analysis of ECG revealed that WIFI induced a combined increase of PR and QT intervals. By contrast, the same exposure failed to alter the maximum amplitude and P waves. After intravenously injection of dopamine (0.50 ml/kg) and epinephrine (0.50ml/kg) under acute exposure to RF we found that WIFI alter catecholamines(dopamine, epinephrine) action on heart variability and blood pressure compared to control. These results suggest for the first time, as far as we know, that exposure to WIFI affect heart rhythm, blood pressure, and catecholamines efficacy on cardiovascular system; indicating that radio frequency can act directly and/or indirectly on the cardiovascular system.

Keywords: heart rate (HR), arterial pressure (PA), electrocardiogram (ECG), the efficacy of catecholamines, dopamine, epinephrine

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Authors: Elda Maraj, Shkelqim Kuka

Abstract:

Coronary heart disease causes many deaths in the world. Unfortunately, this problem will continue to increase in the future. In this paper, a fuzzy logic model to predict coronary heart disease is presented. This model has been developed with seven input variables and one output variable that was implemented for 30 patients in Albania. Here fuzzy logic toolbox of MATLAB is used. Fuzzy model inputs are considered as cholesterol, blood pressure, physical activity, age, BMI, smoking, and diabetes, whereas the output is the disease classification. The fuzzy sets and membership functions are chosen in an appropriate manner. Centroid method is used for defuzzification. The database is taken from University Hospital Center "Mother Teresa" in Tirana, Albania.

Keywords: coronary heart disease, fuzzy logic toolbox, membership function, prediction model

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Authors: Nadia Masood Khan, Muhammad Salman Khan, Gul Muhammad Khan

Abstract:

Cardiologists perform cardiac auscultation to detect abnormalities in heart sounds. Since accurate auscultation is a crucial first step in screening patients with heart diseases, there is a need to develop computer-aided detection/diagnosis (CAD) systems to assist cardiologists in interpreting heart sounds and provide second opinions. In this paper different algorithms are implemented for automated heart sound classification using unsegmented phonocardiogram (PCG) signals. Support vector machine (SVM), artificial neural network (ANN) and cartesian genetic programming evolved artificial neural network (CGPANN) without the application of any segmentation algorithm has been explored in this study. The signals are first pre-processed to remove any unwanted frequencies. Both time and frequency domain features are then extracted for training the different models. The different algorithms are tested in multiple scenarios and their strengths and weaknesses are discussed. Results indicate that SVM outperforms the rest with an accuracy of 73.64%.

Keywords: pattern recognition, machine learning, computer aided diagnosis, heart sound classification, and feature extraction

Procedia PDF Downloads 221