Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 902

Search results for: heart failure.

902 Modeling the Human Cardiovascular System with Aspecial Focus on the Heart Using Dymola

Authors: Stefanie Heinke, Carina Pereira, Jan Spillner, Steffen Leonhardt

Abstract:

Severe heart failure is a common problem that has a significant effect on health expenditures in industrialized countries; moreover it reduces patient-s quality of life. However, current research usually focuses either on detailed modeling of the heart or on detailed modeling of the cardiovascular system. Thus, this paper aims to present a sophisticated model of the heart enhanced with an extensive model of the cardiovascular system. Special interest is on the pressure and flow values close to the heart since these values are critical to accurately diagnose causes of heart failure. The model is implemented in Dymola an object-oriented, physical modeling language. Results achieved with the novel model show overall feasibility of the approach. Moreover, results are illustrated and compared to other models. The novel model shows significant improvements.

Keywords: Cardiovascular system, heart, modeling.

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901 Wavelet-Based Classification of Myocardial Ischemia, Arrhythmia, Congestive Heart Failure and Sleep Apnea

Authors: Santanu Chattopadhyay, Gautam Sarkar, Arabinda Das

Abstract:

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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900 Determination of Myocardial Function Using Heart Accumulated Radiopharmaceuticals

Authors: C. C. D. Kulathilake, M. Jayatilake, T. Takahashi

Abstract:

The myocardium is composed of specialized muscle which relies mainly on fatty acid and sugar metabolism and it is widely contribute to the heart functioning. The changes of the cardiac energy-producing system during heart failure have been proved using autoradiography techniques. This study focused on evaluating sugar and fatty acid metabolism in myocardium as cardiac energy getting system using heart-accumulated radiopharmaceuticals. Two sets of autoradiographs of heart cross sections of Lewis male rats were analyzed and the time- accumulation curve obtained with use of the MATLAB image processing software to evaluate fatty acid and sugar metabolic functions.

Keywords: Autoradiographs, fatty acid, radiopharmaceuticals and sugar.

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899 A New Method in Short-Term Heart Rate Variability — Five-Class Density Histogram

Authors: Liping Li, Ke Li, Changchun Liu, Chengyu Liu, Yuanyang Li

Abstract:

A five-class density histogram with an index named cumulative density was proposed to analyze the short-term HRV. 150 subjects participated in the test, falling into three groups with equal numbers -- the healthy young group (Young), the healthy old group (Old), and the group of patients with congestive heart failure (CHF). Results of multiple comparisons showed a significant differences of the cumulative density in the three groups, with values 0.0238 for Young, 0.0406 for Old and 0.0732 for CHF (p<0.001). After 7 days and 14 days, 46 subjects from the Young and Old groups were retested twice following the same test protocol. Results showed good-to-excellent interclass correlations (ICC=0.783, 95% confidence interval 0.676-0.864). The Bland-Altman plots were used to reexamine the test-retest reliability. In conclusion, the method proposed could be a valid and reliable method to the short-term HRV assessment.

Keywords: Autonomic nervous system, congestive heart failure, heart rate variability, histogram.

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898 Characteristics of Hemodynamics in a Bileaflet Mechanical Heart Valve using an Implicit FSI Method

Authors: Tae-Hyub Hong, Choeng-Ryul Choi, Chang-Nyung Kim

Abstract:

Human heart valves diseased by congenital heart defects, rheumatic fever, bacterial infection, cancer may cause stenosis or insufficiency in the valves. Treatment may be with medication but often involves valve repair or replacement (insertion of an artificial heart valve). Bileaflet mechanical heart valves (BMHVs) are widely implanted to replace the diseased heart valves, but still suffer from complications such as hemolysis, platelet activation, tissue overgrowth and device failure. These complications are closely related to both flow characteristics through the valves and leaflet dynamics. In this study, the physiological flow interacting with the moving leaflets in a bileaflet mechanical heart valve (BMHV) is simulated with a strongly coupled implicit fluid-structure interaction (FSI) method which is newly organized based on the Arbitrary-Lagrangian-Eulerian (ALE) approach and the dynamic mesh method (remeshing) of FLUENT. The simulated results are in good agreement with previous experimental studies. This study shows the applicability of the present FSI model to the complicated physics interacting between fluid flow and moving boundary.

Keywords: Bileaflet Mechanical Heart Valve, Fluid- Structure Interaction.

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897 Statistical Analysis of Failure Cases in Aerospace

Authors: J. H. Lv, W. Z. Wang, S.W. Liu

Abstract:

The major concern in the aviation industry is the flight safety. Although great effort has been put onto the development of material and system reliability, the failure cases of fatal accidents still occur nowadays. Due to the complexity of the aviation system, and the interaction among the failure components, the failure analysis of the related equipment is a little difficult. This study focuses on surveying the failure cases in aviation, which are extracted from failure analysis journals, including Engineering Failure Analysis and Case studies in Engineering Failure Analysis, in order to obtain the failure sensitive factors or failure sensitive parts. The analytical results show that, among the failure cases, fatigue failure is the largest in number of occurrence. The most failed components are the disk, blade, landing gear, bearing, and fastener. The frequently failed materials consist of steel, aluminum alloy, superalloy, and titanium alloy. Therefore, in order to assure the safety in aviation, more attention should be paid to the fatigue failures.

Keywords: Aviation industry, failure analysis, failure component, fatigue.

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896 Feature Selection Approaches with Missing Values Handling for Data Mining - A Case Study of Heart Failure Dataset

Authors: N.Poolsawad, C.Kambhampati, J. G. F. Cleland

Abstract:

In this paper, we investigated the characteristic of a clinical dataseton the feature selection and classification measurements which deal with missing values problem.And also posed the appropriated techniques to achieve the aim of the activity; in this research aims to find features that have high effect to mortality and mortality time frame. We quantify the complexity of a clinical dataset. According to the complexity of the dataset, we proposed the data mining processto cope their complexity; missing values, high dimensionality, and the prediction problem by using the methods of missing value replacement, feature selection, and classification.The experimental results will extend to develop the prediction model for cardiology.

Keywords: feature selection, missing values, classification, clinical dataset, heart failure.

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895 Development of Sleep Quality Index Using Heart Rate

Authors: Dongjoo Kim, Chang-Sik Son, Won-Seok Kang

Abstract:

Adequate sleep affects various parts of one’s overall physical and mental life. As one of the methods in determining the appropriate amount of sleep, this research presents a heart rate based sleep quality index. In order to evaluate sleep quality using the heart rate, sleep data from 280 subjects taken over one month are used. Their sleep data are categorized by a three-part heart rate range. After categorizing, some features are extracted, and the statistical significances are verified for these features. The results show that some features of this sleep quality index model have statistical significance. Thus, this heart rate based sleep quality index may be a useful discriminator of sleep.

Keywords: Sleep, sleep quality, heart rate, statistical analysis.

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894 Detection and Correction of Ectopic Beats for HRV Analysis Applying Discrete Wavelet Transforms

Authors: Desmond B. Keenan

Abstract:

The clinical usefulness of heart rate variability is limited to the range of Holter monitoring software available. These software algorithms require a normal sinus rhythm to accurately acquire heart rate variability (HRV) measures in the frequency domain. Premature ventricular contractions (PVC) or more commonly referred to as ectopic beats, frequent in heart failure, hinder this analysis and introduce ambiguity. This investigation demonstrates an algorithm to automatically detect ectopic beats by analyzing discrete wavelet transform coefficients. Two techniques for filtering and replacing the ectopic beats from the RR signal are compared. One technique applies wavelet hard thresholding techniques and another applies linear interpolation to replace ectopic cycles. The results demonstrate through simulation, and signals acquired from a 24hr ambulatory recorder, that these techniques can accurately detect PVC-s and remove the noise and leakage effects produced by ectopic cycles retaining smooth spectra with the minimum of error.

Keywords: Heart rate variability, vagal tone, sympathetic, parasympathetic, wavelets, ectopic beats, spectral analysis.

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893 An Integrative Bayesian Approach to Supporting the Prediction of Protein-Protein Interactions: A Case Study in Human Heart Failure

Authors: Fiona Browne, Huiru Zheng, Haiying Wang, Francisco Azuaje

Abstract:

Recent years have seen a growing trend towards the integration of multiple information sources to support large-scale prediction of protein-protein interaction (PPI) networks in model organisms. Despite advances in computational approaches, the combination of multiple “omic" datasets representing the same type of data, e.g. different gene expression datasets, has not been rigorously studied. Furthermore, there is a need to further investigate the inference capability of powerful approaches, such as fullyconnected Bayesian networks, in the context of the prediction of PPI networks. This paper addresses these limitations by proposing a Bayesian approach to integrate multiple datasets, some of which encode the same type of “omic" data to support the identification of PPI networks. The case study reported involved the combination of three gene expression datasets relevant to human heart failure (HF). In comparison with two traditional methods, Naive Bayesian and maximum likelihood ratio approaches, the proposed technique can accurately identify known PPI and can be applied to infer potentially novel interactions.

Keywords: Bayesian network, Classification, Data integration, Protein interaction networks.

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892 An Expert System for Car Failure Diagnosis

Authors: Ahmad T. Al-Taani

Abstract:

Car failure detection is a complicated process and requires high level of expertise. Any attempt of developing an expert system dealing with car failure detection has to overcome various difficulties. This paper describes a proposed knowledge-based system for car failure detection. The paper explains the need for an expert system and the some issues on developing knowledge-based systems, the car failure detection process and the difficulties involved in developing the system. The system structure and its components and their functions are described. The system has about 150 rules for different types of failures and causes. It can detect over 100 types of failures. The system has been tested and gave promising results.

Keywords: Expert system, car failure diagnosis, knowledgebasedsystem, CLIPS.

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891 A Diagnostic Fuzzy Rule-Based System for Congenital Heart Disease

Authors: Ersin Kaya, Bulent Oran, Ahmet Arslan

Abstract:

In this study, fuzzy rule-based classifier is used for the diagnosis of congenital heart disease. Congenital heart diseases are defined as structural or functional heart disease. Medical data sets were obtained from Pediatric Cardiology Department at Selcuk University, from years 2000 to 2003. Firstly, fuzzy rules were generated by using medical data. Then the weights of fuzzy rules were calculated. Two different reasoning methods as “weighted vote method" and “singles winner method" were used in this study. The results of fuzzy classifiers were compared.

Keywords: Congenital heart disease, Fuzzy rule-basedclassifiers, Classification

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890 Failure Cases Analysis in Petrochemical Industry

Authors: S. W. Liu, J. H. Lv, W. Z. Wang

Abstract:

In recent years, the failure accidents in petrochemical industry have been frequent, and have posed great security problems in personnel and property. The improvement of petrochemical safety is highly requested in order to prevent re-occurrence of severe accident. This study focuses on surveying the failure cases occurred in petrochemical field, which were extracted from journals of engineering failure, including engineering failure analysis and case studies in engineering failure analysis. The relation of failure mode, failure mechanism, type of components, and type of materials was analyzed in this study. And the analytical results showed that failures occurred more frequently in vessels and piping among the petrochemical equipment. Moreover, equipment made of carbon steel and stainless steel accounts for the majority of failures compared to other materials. This may be related to the application of the equipment and the performance of the material. In addition, corrosion failures were the largest in number of occurrence in the failure of petrochemical equipment, in which stress corrosion cracking accounts for a large proportion. This may have a lot to do with the service environment of the petrochemical equipment. Therefore, it can be concluded that the corrosion prevention of petrochemical equipment is particularly important.

Keywords: Cases analysis, corrosion, failure, petrochemical industry.

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889 A Universal Approach to Categorize Failures in Production

Authors: K. Knüppel, G. Meyer, P. Nyhuis

Abstract:

The increasing interconnectedness and complexity of  production processes raise the susceptibility of production systems to  failure. Therefore, the ability to respond quickly to failures is  increasingly becoming a competitive factor. The research project  "Sustainable failure management in manufacturing SMEs" is  developing a methodology to identify failures in the production and  select preventive and reactive measures in order to correct failures  and to establish sustainable failure management systems.

 

Keywords: Failure categorization, failure management, logistic performance, production optimization.

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888 Quantification of Heart Rate Variability: A Measure based on Unique Heart Rates

Authors: V. I. Thajudin Ahamed, P. Dhanasekaran, A. Naseem, N. G. Karthick, T. K. Abdul Jaleel, Paul K.Joseph

Abstract:

It is established that the instantaneous heart rate (HR) of healthy humans keeps on changing. Analysis of heart rate variability (HRV) has become a popular non invasive tool for assessing the activities of autonomic nervous system. Depressed HRV has been found in several disorders, like diabetes mellitus (DM) and coronary artery disease, characterised by autonomic nervous dysfunction. A new technique, which searches for pattern repeatability in a time series, is proposed specifically for the analysis of heart rate data. These set of indices, which are termed as pattern repeatability measure and pattern repeatability ratio are compared with approximate entropy and sample entropy. In our analysis, based on the method developed, it is observed that heart rate variability is significantly different for DM patients, particularly for patients with diabetic foot ulcer.

Keywords: Autonomic nervous system, diabetes mellitus, heart rate variability, pattern identification, sample entropy

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887 On The Analysis of a Compound Neural Network for Detecting Atrio Ventricular Heart Block (AVB) in an ECG Signal

Authors: Salama Meghriche, Amer Draa, Mohammed Boulemden

Abstract:

Heart failure is the most common reason of death nowadays, but if the medical help is given directly, the patient-s life may be saved in many cases. Numerous heart diseases can be detected by means of analyzing electrocardiograms (ECG). Artificial Neural Networks (ANN) are computer-based expert systems that have proved to be useful in pattern recognition tasks. ANN can be used in different phases of the decision-making process, from classification to diagnostic procedures. This work concentrates on a review followed by a novel method. The purpose of the review is to assess the evidence of healthcare benefits involving the application of artificial neural networks to the clinical functions of diagnosis, prognosis and survival analysis, in ECG signals. The developed method is based on a compound neural network (CNN), to classify ECGs as normal or carrying an AtrioVentricular heart Block (AVB). This method uses three different feed forward multilayer neural networks. A single output unit encodes the probability of AVB occurrences. A value between 0 and 0.1 is the desired output for a normal ECG; a value between 0.1 and 1 would infer an occurrence of an AVB. The results show that this compound network has a good performance in detecting AVBs, with a sensitivity of 90.7% and a specificity of 86.05%. The accuracy value is 87.9%.

Keywords: Artificial neural networks, Electrocardiogram(ECG), Feed forward multilayer neural network, Medical diagnosis, Pattern recognitionm, Signal processing.

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886 Hemocompatible Thin-Film Materials Recreating the Structure of the Cell Niches with High Potential for Endothelialization

Authors: Roman Major, Klaudia Trembecka-Wojciga, Juergen Markus Lackner, Boguslaw Major

Abstract:

The future and the development of science is therefore seen in interdisciplinary areas such as biomedical engineering. Selfassembled structures, similar to stem cell niches would inhibit fast division process and subsequently capture the stem cells from the blood flow. By means of surface topography and the stiffness as well as microstructure progenitor cells should be differentiated towards the formation of endothelial cells monolayer which effectively will inhibit activation of the coagulation cascade. The idea of the material surface development met the interest of the clinical institutions, which support the development of science in this area and are waiting for scientific solutions that could contribute to the development of heart assist systems. This would improve the efficiency of the treatment of patients with myocardial failure, supported with artificial heart assist systems. Innovative materials would enable the redesign, in the post project activity, construction of ventricular heart assist.

Keywords: Bio-inspired materials, electron microscopy, haemocompatibility, niche-like structures, thin coatings.

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885 The Service Failure and Recovery in the Information Technology Services

Authors: Jun Luo, Weiguo Zhang., Dabin Qin

Abstract:

It is important to retain customer satisfaction in information technology services. When a service failure occurs, companies need to take service recovery action to recover their customer satisfaction. Although companies cannot avoid all problems and complaints, they should try to make up. Therefore, service failure and service recovery have become an important and challenging issue for companies. In this paper, the literature and the problems in the information technology services were reviewed. An integrated model of profit driven for the service failure and service recovery was established in view of the benefit of customer and enterprise. Moreover, the interaction between service failure and service recovery strategy was studied, the result of which verified the matching principles of the service recovery strategy and the type of service failure. In addition, the relationship between the cost of service recovery and customer-s cumulative value of service after recovery was analyzed with the model. The result attributes to managers in deciding on appropriate resource allocations for recovery strategies.

Keywords: service failure, service recovery, informationtechnology services

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884 A Bathtub Curve from Nonparametric Model

Authors: Eduardo C. Guardia, Jose W. M. Lima, Afonso H. M. Santos

Abstract:

This paper presents a nonparametric method to obtain the hazard rate “Bathtub curve” for power system components. The model is a mixture of the three known phases of a component life, the decreasing failure rate (DFR), the constant failure rate (CFR) and the increasing failure rate (IFR) represented by three parametric Weibull models. The parameters are obtained from a simultaneous fitting process of the model to the Kernel nonparametric hazard rate curve. From the Weibull parameters and failure rate curves the useful lifetime and the characteristic lifetime were defined. To demonstrate the model the historic time-to-failure of distribution transformers were used as an example. The resulted “Bathtub curve” shows the failure rate for the equipment lifetime which can be applied in economic and replacement decision models.

Keywords: Bathtub curve, failure analysis, lifetime estimation, parameter estimation, Weibull distribution.

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883 Evaluation Process for the Hardware Safety Integrity Level

Authors: Sung Kyu Kim, Yong Soo Kim

Abstract:

Safety instrumented systems (SISs) are becoming increasingly complex and the proportion of programmable electronic parts is growing. The IEC 61508 global standard was established to ensure the functional safety of SISs, but it was expressed in highly macroscopic terms. This study introduces an evaluation process for hardware safety integrity levels through failure modes, effects, and diagnostic analysis (FMEDA).FMEDA is widely used to evaluate safety levels, and it provides the information on failure rates and failure mode distributions necessary to calculate a diagnostic coverage factor for a given component. In our evaluation process, the components of the SIS subsystem are first defined in terms of failure modes and effects. Then, the failure rate and failure mechanism distribution are assigned to each component. The safety mode and detectability of each failure mode are determined for each component. Finally, the hardware safety integrity level is evaluated based on the calculated results.

Keywords: Safety instrumented system; Safety integrity level; Failure modes, effects, and diagnostic analysis; IEC 61508.

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882 Seismic Behaviour of Romanian Ortodox Churches, Modeling of Failure Modes by Rigid Blocks

Authors: Marius Mosoarca, Victor Gioncu, Ovidiu Cosma

Abstract:

Historic religious buildings located in seismic areas have developed different failure mechanisms. Simulation of failure modes is done with computer programs through a nonlinear dynamic analysis or simplified using the method of failure blocks. Currently there are simulation methodologies of failure modes based on the failure rigid blocks method only for Roman Catholic churches type. Due to differences of shape in plan, elevation and construction systems between Orthodox churches and Catholic churches, for the first time there were initiated researches in the development of this simulation methodology for Orthodox churches. In this article are presented the first results from the researches. The theoretical results were compared with real failure modes recorded at an Orthodox church from Banat region, severely damaged by earthquakes in 1991. Simulated seismic response, using a computer program based on finite element method was confirmed by cracks after earthquakes. The consolidation of the church was made according to these theoretical results, realizing a rigid floor connecting all the failure blocks.

Keywords: Dinamic analysis, failure mechanism, rigid blocks seismic simulation.

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881 Finite Element Prediction of Hip Fracture during a Sideways Fall

Authors: M. Ikhwan Z. Ridzwan, Bidyut Pal, Ulrich N. Hansen

Abstract:

Finite element method was applied to model damage development in the femoral neck during a sideways fall. The femoral failure was simulated using the maximum principal strain criterion. The evolution of damage was consistent with previous studies. It was initiated by compressive failure at the junction of the superior aspect of the femoral neck and the greater trochanter. It was followed by tensile failure that occurred at the inferior aspect of the femoral neck before a complete transcervical fracture was observed. The estimated failure line was less than 50° from the horizontal plane (Pauwels type II).

Keywords: Femoral Strength, Finite Element Models, Hip Fracture, Progressive Failure, Sideways Fall.

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880 Automatic Classification of Periodic Heart Sounds Using Convolutional Neural Network

Authors: Jia Xin Low, Keng Wah Choo

Abstract:

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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879 Adaptive Filtering of Heart Rate Signals for an Improved Measure of Cardiac Autonomic Control

Authors: Desmond B. Keenan, Paul Grossman

Abstract:

In order to provide accurate heart rate variability indices of sympathetic and parasympathetic activity, the low frequency and high frequency components of an RR heart rate signal must be adequately separated. This is not always possible by just applying spectral analysis, as power from the high and low frequency components often leak into their adjacent bands. Furthermore, without the respiratory spectra it is not obvious that the low frequency component is not another respiratory component, which can appear in the lower band. This paper describes an adaptive filter, which aids the separation of the low frequency sympathetic and high frequency parasympathetic components from an ECG R-R interval signal, enabling the attainment of more accurate heart rate variability measures. The algorithm is applied to simulated signals and heart rate and respiratory signals acquired from an ambulatory monitor incorporating single lead ECG and inductive plethysmography sensors embedded in a garment. The results show an improvement over standard heart rate variability spectral measurements.

Keywords: Heart rate variability, vagal tone, sympathetic, parasympathetic, spectral analysis, adaptive filter.

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878 An Investigation of Shipping Comb Failures due to usage in Manufacturing Processes using RCFA and FMEA

Authors: Atjanakul W, Chutima S., Kamnerdthong T.

Abstract:

Shipping comb is mounted on Head Stack Assembly (HSA) to prevent collision of the heads, maintain the gap between suspensions and protect HSA tips from unintentional contact damaged in the manufacturing process. Failure analysis of shipping comb in hard disk drive production processes is proposed .Field observations were performed to determine the fatal areas on shipping comb and their failure fraction. Root cause failure analysis (RCFA) is applied to specify the failure causes subjected to various loading conditions. For reliability improvement, failure mode and effects analysis (FMEA) procedure to evaluate the risk priority is performed. Consequently, the more suitable information design criterions were obtained.

Keywords: Shipping comb, Hard disk drive, Root cause failureanalysis, Failure mode and effects analysis

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877 HRV Analysis Based Arrhythmic Beat Detection Using kNN Classifier

Authors: Onder Yakut, Oguzhan Timus, Emine Dogru Bolat

Abstract:

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.

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876 A Partially Accelerated Life Test Planning with Competing Risks and Linear Degradation Path under Tampered Failure Rate Model

Authors: Fariba Azizi, Firoozeh Haghighi, Viliam Makis

Abstract:

In this paper, we propose a method to model the relationship between failure time and degradation for a simple step stress test where underlying degradation path is linear and different causes of failure are possible. It is assumed that the intensity function depends only on the degradation value. No assumptions are made about the distribution of the failure times. A simple step-stress test is used to shorten failure time of products and a tampered failure rate (TFR) model is proposed to describe the effect of the changing stress on the intensities. We assume that some of the products that fail during the test have a cause of failure that is only known to belong to a certain subset of all possible failures. This case is known as masking. In the presence of masking, the maximum likelihood estimates (MLEs) of the model parameters are obtained through an expectation-maximization (EM) algorithm by treating the causes of failure as missing values. The effect of incomplete information on the estimation of parameters is studied through a Monte-Carlo simulation. Finally, a real example is analyzed to illustrate the application of the proposed methods.

Keywords: Expectation-maximization (EM) algorithm, cause of failure, intensity, linear degradation path, masked data, reliability function.

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875 Cardiac Disorder Classification Based On Extreme Learning Machine

Authors: Chul Kwak, Oh-Wook Kwon

Abstract:

In this paper, an extreme learning machine with an automatic segmentation algorithm is applied to heart disorder classification by heart sound signals. From continuous heart sound signals, the starting points of the first (S1) and the second heart pulses (S2) are extracted and corrected by utilizing an inter-pulse histogram. From the corrected pulse positions, a single period of heart sound signals is extracted and converted to a feature vector including the mel-scaled filter bank energy coefficients and the envelope coefficients of uniform-sized sub-segments. An extreme learning machine is used to classify the feature vector. In our cardiac disorder classification and detection experiments with 9 cardiac disorder categories, the proposed method shows significantly better performance than multi-layer perceptron, support vector machine, and hidden Markov model; it achieves the classification accuracy of 81.6% and the detection accuracy of 96.9%.

Keywords: Heart sound classification, extreme learning machine

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874 Non-Circular Carbon Fiber Reinforced Polymers Chainring Failure Analysis

Authors: A. Elmikaty, Z. Thanawarothon, L. Mezeix

Abstract:

This paper presents a finite element model to simulate the teeth failure of non-circular composite chainring. Model consists of the chainring and a part of the chain. To reduce the size of the model, only the first 11 rollers are simulated. In order to validate the model, it is firstly applied to a circular aluminum chainring and evolution of the stress in the teeth is compared with the literature. Then, effect of the non-circular shape is studied through three different loading positions. Strength of non-circular composite chainring and failure scenario is investigated. Moreover, two composite lay-ups are proposed to observe the influence of the stacking. Results show that composite material can be used but the lay-up has a large influence on the strength. Finally, loading position does not have influence on the first composite failure that always occurs in the first tooth.

Keywords: CFRP, composite failure, FEA, non-circular chainring.

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873 Design and Simulation of Heartbeat Measurement System Using Arduino Microcontroller in Proteus

Authors: Muhibul H. Bhuyan, Mafujul Hasan

Abstract:

If a person can monitor his/her heart rate regularly then he/she can detect heart disease early and thus he/she can enjoy longer life span. Therefore, this disease should be taken seriously. Hence, many health care devices and monitoring systems are being designed to keep track of the heart disease. This work reports a design and simulation processes of an Arduino microcontroller based heart rate measurement and monitoring system in Proteus environment. Clipping sensors were utilized to sense the heart rate of an individual from the finger tips. It is a digital device and uses mainly infrared (IR) transmitter (mainly IR LED) and receiver (mainly IR photo-transistor or IR photo-detector). When the heart pumps the blood and circulates it among the blood vessels of the body, the changed blood pressure is detected by the transmitter and then reflected back to the receiver accordingly. The reflected signals are then processed inside the microcontroller through a software written assembly language and appropriate heart rate (HR) is determined by it in beats per minute (bpm) from the detected signal for a duration of 10 seconds and display the same in bpm on the LCD screen in digital format. The designed system was simulated on several persons with varying ages, for example, infants, adult persons and active athletes. Simulation results were found very satisfactory.

Keywords: Heart rate measurement, design, simulation, Proteus, Arduino Uno microcontroller.

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