Science topic
Heart Sounds - Science topic
The sounds heard over the cardiac region produced by the functioning of the heart. There are four distinct sounds: the first occurs at the beginning of SYSTOLE and is heard as a "lubb" sound; the second is produced by the closing of the AORTIC VALVE and PULMONARY VALVE and is heard as a "dupp" sound; the third is produced by vibrations of the ventricular walls when suddenly distended by the rush of blood from the HEART ATRIA; and the fourth is produced by atrial contraction and ventricular filling.
Publications related to Heart Sounds (6,228)
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With the development of big data techniques, the difficulty that streaming longitudinal data lack theoretical support in modeling has become increasingly prominent. This paper proposes a two-layer Gaussian mixture model within a Bayesian framework to theoretically fit such data by characterizing their nature, such as being correlated, time-varying,...
This paper explores the historical and technological evolution of the stethoscope, emphasizing its role as a communication device in the medical field. The research begins by examining the cultural significance of sound and listening, drawing on literary and historical context provided by sound, culture, and medical historians. The concept of audil...
Background
Pericardial effusion is a severe complication of pediatric paragonimiasis, necessitating a careful approach to diagnosis and treatment. Traditionally, the management of pericardial effusion pericardial effusion due to paragonimiasis has involved surgical intervention to drain the accumulated fluid, especially in severe cases. However, th...
Pre-trained deep learning models, known as foundation models, have become essential building blocks in machine learning domains such as natural language processing and image domains. This trend has extended to respiratory and heart sound models, which have demonstrated effectiveness as off-the-shelf feature extractors. However, their evaluation ben...
ABSTRACT
Automated analysis of foetal phonocardiogram (foetal PCG) signals can provide valuable insights into the health
and development of the fetus during pregnancy. The system employs Continuous Wavelet Transform (CWT),
Short-Time Fourier Transform (STFT), and Empirical Mode Decomposition (EMD) to extract relevant features
from PCG signals. C...
Cardiovascular diseases (CVDs) pose a significant threat to human health and place considerable strain on healthcare systems. Therefore, it is crucial to maximize the acquisition of cardiovascular information (CVI) through non-invasive methods to enhance early screening, diagnosis, and evaluation of CVDs. Numerous studies have demonstrated that obt...
Classification of biomedical sounds using Artificial Intelligence (AI), especially the examination of heart sounds, is of great importance. However, existing feature extraction methods often fall short in performance due to their limited capacity for frequency analysis and potential information loss. This study proposes a novel feature extraction m...
Tuberculosis remains a major public health issue in Morocco. Pulmonary tuberculosis is the most common form, but various extrapulmonary forms exist. Tuberculous pericarditis is a rare form of extrapulmonary tuberculosis that can be complicated by cardiac tamponade, pericardial constriction, or their combination, which can threaten the patient's lif...
Objective: Large artery stiffening leads to an increase in cardiovascular risk and organ damage of the kidneys, brain or the heart. Biomarkers that allow for early detection of this phenomenon are a point of interest in research, with pulse-wave velocity (PWV) having been proven useful in predicting and monitoring arterial stiffness. We previously...
Objective: To classify lung (LS) and heart (HS) sounds between healthy and diseased subjects using a GMM-HMM model. Theoretical Framework: Feature extractors highlight class differences, in this case two types of acoustic vectors were used: MFCC and quantiles. In addition, it is important to determine the number of clusters in the data, in order to...
Early and accurate diagnosis of heart conditions is pivotal for effective treatment. Phonocardiography (PCG) has become a standard diagnostic tool for evaluating and detecting cardiac abnormalities. While traditional cardiac auscultation remains widely used, its accuracy is highly dependent on the clinician’s experience and auditory skills. Consequ...
Tuberculosis remains a major public health issue in Morocco. Pulmonary tuberculosis is the most common form, but various extrapulmonary forms exist. Tuberculous pericarditis is a rare form of extrapulmonary tuberculosis that can be complicated by cardiac tamponade, pericardial constriction, or their combination, which can threaten the patient's lif...
Worldwide, heart disease is the leading cause of mortality. Cardiac auscultation, when conducted by a trained professional, is a non-invasive, cost-effective, and readily available method for the initial assessment of cardiac health. Automated heart sound analysis offers a promising and accessible approach to supporting cardiac diagnosis. This work...
Millions of people worldwide suffer from heart failure, which is a serious public health concern that results in high medical costs from prolonged hospital stay. This study aimed to assess the determinant factors associated with prolonged hospitalization among admitted acute heart failure at Jimma Medical Center, south west Ethiopia. The study was...
Congenital heart disease (CHD) is one of the most common congenital birth defects. With the deepening of people’s understanding of CHD disease and the continuous improvement of screening methods, children with CHD have been able to receive diagnosis and treatment at an early stage, thus improving the survival rate and quality of life. The main mean...
Since Cardiac and vascular conditions rank among major cause of death around the world, sophisticated diagnostic methods are required for both early identification and prevention [13] Libby et al. In order to predict heart functionality with high accuracy, we present a novel deep learning model in this study that uses heart acoustic inputs. Due to...
This study presents a comprehensive analysis of foetal phonocardiography (fPCG) signals obtained from the Indian Institute of Science foetal Heart Sound Database (IIScFHSDB). The study evaluates statistical features like amplitude range, mean and standard deviation along with spectral features like low and high frequency power. These features are c...
A heart murmur is an atypical sound produced by blood flow through the heart. It can indicate a serious heart condition, so detecting heart murmurs is critical for identifying and managing cardiovascular diseases. However, current methods for identifying murmurous heart sounds do not fully utilize the valuable insights that can be gained by explori...
Penetrating cardiac injuries are life-threatening emergencies requiring immediate surgical intervention. We presented a case of cardiac stab wound leading to cardiac tamponade and rupture of the pulmonary artery and right ventricle who survived long enough to undergo emergency procedure. A 25-year-old male was stabbed in the left chest approximatel...
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Biometrics has been increasingly integrated into wearables for enhanced data security in recent years. Meanwhile, wearable popularity offers a unique chance to capture novel biometrics via embedded sensors. In this paper, we study new intracorporal biometrics combining the uniqueness of heart motion, bone conduction, and body asymmetry. Specificall...
Cardiovascular diseases are non-communicable diseases that are considered the leading cause of death worldwide accounting for 17.9 million fatalities. Auscultation of heart sounds is the most common and valuable way of diagnosing heart diseases. Normal heart sounds have a special rhythmic pattern as an indicator of heart integrity. Many experts con...
Ensuring spiritual health/security require community-oriented theory. Study was conducted with the aim of designing and validating the theory of compassionate spiritual governance of mentors with sound heart for promoting spiritual health and spiritual security of society. This study was conducted based on the Creswell model and the qualitative der...
Heart valve disease has a large and growing burden, with a prognosis worse than many cancers. Screening with a traditional stethoscope is underutilised, often inaccurate even in skilled hands, and requires time-consuming, intimate examinations. Here, we present a handheld device to enable untrained users to record high-quality heart sounds without...
Intelligent heart sound diagnosis based on Convolutional Neural Networks (CNN) has been attracting increasing attention due to its accuracy and efficiency, which have been improved by recent studies. However, the performance of CNN models, heavily influenced by their parameters and structures, still has room for improvement. In this paper, we propo...
Objective
Physical assessment is an indispensable and pivotal skill that nurses must aptly monitor, evaluate, and deliver timely care, particularly in the context of critically ill patients. However, studies have revealed instances where nurses demonstrate inaccurate practices. This study is aimed to measure the physical assessment skills of critic...
Speech processing is emerging as an important application area of digital signal processing. In this paper, we present a performance comparison evaluation for patient classification based on Mel Frequency Cepstrum Coefficient (MFCC) using deep learning in the field of speech recognition. We conduct research by heart sound data of patients and healt...
Cardiovascular diseases (CVDs) are the leading cause of death worldwide, claiming over 17 million lives annually. Early detection of conditions like heart murmurs, often indicative of heart valve abnormalities, is critical for improving patient outcomes. Traditional diagnostic methods, including physical auscultation and advanced imaging techniques...
Forcecardiography (FCG) uses force sensors to record the mechanical vibrations induced on the chest wall by cardiac and respiratory activities. FCG is usually performed via piezoelectric lead-zirconate titanate (PZT) sensors, which simultaneously record the very slow respiratory movements of the chest, the slow infrasonic vibrations due to emptying...
The implementation of noncontact vital sign monitoring in real-world scenarios is still facing a number of challenges, including the need to deal with multitarget scenarios, optimal measurement location, and precise cardiac activity monitoring. This article examines the potential of different body locations for vital signs monitoring and uses a mor...
This study focuses on the evaluation of cardiotoxicity during radiotherapy for breast cancer. The background of the study is that radiotherapy is widely used in the treatment of breast cancer but may cause cardiotoxicity, especially radiation myocarditis, which poses a threat to the long-term quality of life of patients. The subject of this study i...
This dataset comprises phonocardiogram (PCG) signals, blood pressure measurements, and additional demographics collected from 78 participants under controlled conditions. The data were recorded using a medical-grade digital stethoscope and automated blood pressure monitor to ensure precision and consistency. PCG signals were captured at the Pulmoni...
Objective: PCG represents the acoustic replay of heart sounds from the cardiac structure. To detect and analyse the different conditions of the heart, heart sound signals are essential. CVD is detected by classifiers who superficially identify the cardiac features. Abnormal sounds in systole or diastole could indicate valve stenosis or regurgitatio...
There are already many analyses of heart sounds used to develop diagnostic systems for the heart condition. However, the existing heart sound database state is not sufficient to train a large number of deep learning models and is not balanced-the normal heart sounds are always more present than abnormal heart sounds. Hence, we are interested in alg...
To effectively identify and differentiate between different heart problems based on heart sound signals, and to assist clinicians in diagnosing various heart conditions. Heart sound signal analysis is crucial for the early diagnosis of heart diseases. A heart sound segmentation method is proposed that incorporates heart sound envelopes and time-fre...
This study explores the application of Vision Transformer (ViT) principles in audio analysis, specifically focusing on heart sounds. This paper introduces ENACT-Heart - a novel ensemble approach that leverages the complementary strengths of Convolutional Neural Networks (CNN) and ViT through a Mixture of Experts (MoE) framework, achieving a remarka...
Principles of Spiritual Medicine", the application of Sound Heart theory in teaching spiritual health to medical students
Abstract
Aim: Evidence indicates the health system need for spiritual health services based on the scientific theory and the need for student education. The aim of this study was designing of spiritual health services competence...
Stuck mechanical heart valves had always been tricky to manage and there has been always a debate on how to proceed with management plan. There is uncertainty regarding the type of thrombolytic agent, its dose, and rate of administration. We are reporting a case of stuck mitral valve with extremely low left ventricular ejection fraction (LVEF) whic...
Worldwide, 65 million third-quarter MFIUs take place each year, 98% of them located in countries with low Gross Industrial Product. The objective is to determine the factors associated with intrauterine fetal death in the Bunyakiri Rural Health Zone. Material and methods: this is a retrospective cross-sectional study carried out on 73 parturients w...
This study proposes a multimodal fusion framework for heart disease classification that combines multiple spectral analyses of heart sounds with clinical metadata. Our framework integrates four complementary spectral analysis methods (Stockwell transform, bispectrum, mel-spectrogram, and power spectrum) using Vision Transformers. This spectral fusi...
Objective: More attention should be paid to glucose metabolism in children with Williams-Beuren syndrome (WBS). Methods: The clinical data of a child diagnosed with WBS due to diabetic ketoacidosis (DKA) were retrospectively analyzed, and the related literature was reviewed. Results: An 8-year-old boy presented with thickened upper lip, low palatal...
Phonocardiograms (PCG) provide a non-invasive approach to analyzing heart sounds, making them vital for the early detection of cardiac issues. However, identifying the most effective machine learning models and feature extraction techniques for classifying PCG signals remains a challenge. This study aims to determine the most efficient and accurate...
Aims
Smartphones have recently been utilized to measure heart sounds in the general population, but not yet in real-world hospital settings. This study aims to assess the feasibility of smartphones for heart sound measurement across various hospital departments and to identify the factors causing suboptimal heart sound measurements.
Methods and re...
Background and Objective: Spiritual health and spiritual security of the community require educational-therapeutic services based on community-oriented theory. Policies should be consistent with the social and cultural aspects of the society. This study was conducted with the aim of designing and validating the theory of compassionate spiritual gov...
Recent advances in traditional “-omics” technologies have provided deeper insights into cardiovascular diseases through comprehensive molecular profiling. Accordingly, digitalomics has emerged as a novel transdisciplinary concept that integrates multimodal information with digitized physiological data, medical imaging, environmental data, electroni...
The detection of cardiovascular diseases through the analysis of phonocardiograms (PCGs), which are digital recordings of heartbeat sounds, is crucial for early diagnosis. Conventional feature extraction methods often face challenges in distinguishing non-stationary signals like healthy and pathological PCG signals. Our research addresses these cha...
Anomaly detection is a typical binary classification problem under the condition of unbalanced samples, which has been widely used in various fields of data mining. For example, it can help detect heart murmurs when the heart is structurally abnormal, to tell if a newborn has congenital heart disease. Due to the low time and high efficiency, most w...
Laubry-Pezzi syndrome (L-PS) is a rare congenital heart disease characterized by a ventricular septal defect (VSD) and aortic valve prolapse. These cardiac lesions predispose individuals to infective endocarditis (IE), a life-threatening complication, especially in resource-constrained settings. A 17-year-old male presented with a three-week histor...
Large language models (LLMs) for audio have excelled in recognizing and analyzing human speech, music, and environmental sounds. However, their potential for understanding other types of sounds, particularly biomedical sounds, remains largely underexplored despite significant scientific interest. In this study, we focus on diagnosing cardiovascular...
Tuberculosis remains a major public health issue in Morocco. Pulmonary tuberculosis is the most common form, but various extrapulmonary forms exist. Tuberculous pericarditis is a rare form of extrapulmonary tuberculosis that can be complicated by cardiac tamponade, pericardial constriction, or their combination, which can threaten the patient's lif...
Heart sounds, or phonocardiograms (PCG), are important for diagnosing cardiovascular conditions, providing a non-invasive means to assess heart function through auscultation. Accurate classification of PCG signals can facilitate early detection of cardiac abnormalities, significantly improving patient outcomes. However, the complexity and variabili...
Phonocardiogram (PCG) signal is the digital sound recording of various heart sounds. To diagnose the different types of heart disorders, it is often necessary to analyse these PCG signals. However, PCG signal recording is challenging due to disturbing surrounding noise signals. So denoising the PCG signal is done before using PCG for advanced proce...
Background: Purring in cats can interfere with cardiac auscultation. If the produced noise is loud enough, purring makes it impossible to perform a meaningful auscultation as it is much louder than heart sounds and murmurs. Our study introduced and tested a new, simple, fear-free, cat-friendly method to stop purring during auscultation. Methods: Th...
Fetal phonocardiography is a well-known auscultation technique for evaluation of fetal health. However, murmurs that are synchronous with the maternal heartbeat can often be heard while listening to fetal heart sounds. Maternal placental murmurs (MPM) could be used to detect maternal cardiovascular and placental abnormalities, but the recorded MPMs...
The alarming prevalence and mortality rates associated with cardiovascular diseases have emphasized the urgency for innovative detection solutions. Traditional methods, often costly, bulky, and prone to subjectivity, fall short of meeting the need for daily monitoring. Digital and portable wearable monitoring devices have emerged as a promising res...
Introduction
Sleep deprivation (SD) significantly disrupts the homeostasis of the cardiac-brain axis, yet the neuromodulation effects of deep magnetic stimulation (DMS), a non-invasive and safe method, remain poorly understood.
Methods
Sixty healthy adult males were recruited for a 36-h SD study, they were assigned to the DMS group or the control...
In cardiology, the study of heart sounds is an essential diagnostic tool. Heart sound segmentation is used to automatically analyse phonocardiogram signals(PCG). This provides relevant information for diagnosis and increases the accuracy of identification. This paper presents a method for automatic segmentation of S1 and S2 heart sounds based on th...
Introduction
Cardiac tamponade is a life-threatening condition resulting from fluid accumulation in the pericardial sac, leading to decreased cardiac output and shock. Various etiologies can cause cardiac tamponade, including liver cirrhosis, which may be induced by autoimmune hepatitis. Autoimmune hepatitis is a chronic inflammatory liver disease...
This work introduces an innovative method for heart sound recognition using a hybrid joint transform correlator (JTC). Traditional techniques such as convolutional neural networks and machine learning models, although promising, often suffer from computational complexity and latency issues, resulting in slower processing speeds. In contrast, the pr...
Objective
Congenital heart disease with pulmonary arterial hypertension (CHD-PAH), caused by CHD, is associated with high clinical mortality. Hence, timely diagnosis is imperative for treatment.
Approach
Two non-invasive diagnosis algorithms of CHD-PAH were put forward in this review, which were direct three-divided and two-stage classification mo...
Cardiac auscultation using a digital stethoscope is an important method for diagnosis of cardiovascular diseases (CVDs). However, heart sound recordings are often contaminated with adventitious noise, especially in crowded, noisy settings such as resource-constrained hospitals. This noise can confound accurate diagnosis of heart pathologies. We pro...
Cardiovascular diseases currently pose the greatest threat to human health and future predicament is uncertain. Since most heart-related problems are reflected by the small variations in the heart’s sounds, quality research into heart rhythm will provide valuable health information that may identify and treat cardiac-related issues and disorders. D...
Heart and lung sounds are crucial for healthcare monitoring. Recent improvements in stethoscope technology have made it possible to capture patient sounds with enhanced precision. In this dataset, we used a digital stethoscope to capture both heart and lung sounds, including individual and mixed recordings. To our knowledge, this is the first datas...
Pericarditis refers to inflammation of the pericardium, often
accompanied by the accumulation of serous or fibrinous
inflammatory substances. In cattle, it is almost exclusively
caused by a foreign object from the reticulum penetrating
the reticular wall, diaphragm, and pericardial sac. Key signs
of pericarditis include tachycardia, muffled heart s...
This paper seeks to enhance the performance of Mel Frequency Cepstral Coefficients (MFCCs) for detecting abnormal heart sounds. Heart sounds are first pre-processed to remove noise and then segmented into S1, systole, S2, and diastole intervals, with thirteen MFCCs estimated from each segment, yielding 52 MFCCs per beat. Finally, MFCCs are used for...
Digital medical instruments are essential in today's world to make fast and precise diagnoses. By combining several features into a single device, healthcare can be provided more affordably and with greater patient care and medical efficiency. This project describes the development of a cost-effective digital stethoscope featuring an integrated oxi...
Late‑presenting congenital diaphragmatic hernia (CDH) is an unusual case. It rarely appears apart from the neonate. We report the case of a 3‑month‑old male infant presented with a history of recurrent chest infections and breathlessness for the past 4 days. Examination revealed the signs of respiratory distress in the form of subtitles and tachypn...
Background
Spinal cord injury (SCI) often leads to the loss of urinary sensation, making urination difficult. In a previous experiment involving six healthy participants, we measured heartbeat-induced acoustic pulse waves (HAPWs) at the mid-back, calculated time-series power spectra of heart rate gradients at three ultralow/very low frequencies, di...
A 54-year-old man presented with a significant fourth heart sound (S4) and increased intensity of the second heart sound (S2), despite the absence of heart failure symptoms, in the second week of March 2024. Visualized phonocardiograms confirmed these findings, and further interviews revealed that he had suffered lifestyle changes, such as long com...
The automatic diagnosis of heart problems requires a deep understanding of murmurs that indicate various cardiac pathologies. We propose a novel analysis method focusing on systolic murmurs in heart sounds, using a multiresolution complex Gabor dictionary. The dictionary consists of localized complex-valued Gabor functions with various time-frequen...
In the ever-evolving landscape of medical diagnostics, this study details the systematic design process and concept selection methodology for developing an advanced digital stethoscope, demonstrating the evolution from traditional acoustic models to AI-enhanced digital solutions. The device integrates cutting-edge AI technology with traditional aus...
An investigation indicated that one out of every four deaths is caused by cardiovascular disease. Early detection of some illnesses can help save lives, and increasing awareness of heart health can do just that. It has been proven that cardiology specialists can predict the likelihood of a heart attack with about 67% accuracy. Our ultimate objectiv...
A 2.5-year-old male child from a poor socioeconomic background, exhibiting typical developmental milestones, presented with multiple painful masses on the left side of neck, left axilla, and upper chest, persisting for the past 5-6 months (Fig. 1a). The overlying skin showed ulcera-tion with bloody-mucoid discharge. At first, the swellings appeared...
Objective:
Phonocardiography has recently gained popularity in low-cost and remote monitoring, including passive fetal heart monitoring. The development of methods which analyse phonocardiographic data tries to capitalize on this opportunity, and in recent years a multitude of such algorithms and models have been published. In these approaches the...
This article includes a literature review and a case study of artificial intelligence (AI) heart murmur detection models to analyse the opportunities and challenges in deploying AI in cardiovascular healthcare in low- or medium-income countries (LMICs). This study has two parallel components: (1) The literature review assesses the capacity of AI to...
Background: The goal of Iran's health system is developing the spiritual health of the society affected by the social determinants of health. The aim of the study was providing a "policy brief" to adjust the social determinants of the spiritual health of the community.
Methods: A two-stage qualitative study included Islamic future research based on...
Background
Andersen-Tawil syndrome (ATS) is a rare autosomal dominant disorder caused by variants in the KCNJ2 gene. It is associated with periodic paralysis, dysmorphic features and cardiac arrhythmias. The syndrome exhibits incomplete penetrance, leading to a broad spectrum of clinical manifestations, making diagnosis challenging.
Case descripti...
Given the global prevalence of cardiovascular diseases, there is a pressing need for easily accessible early screening methods. Typically, this requires medical practitioners to investigate heart auscultations for irregular sounds, followed by echocardiography and electrocardiography tests. To democratize early diagnosis, we present a user-friendly...
Cardiovascular diseases remain a leading global cause of mortality, underscoring the urgent need for intelligent diagnostic tools to enhance early detection, prediction, diagnosis, prevention, treatment, and recovery. This demand has spurred the advancement of wearable and flexible technologies, revolutionizing continuous, noninvasive, and remote h...
Analysis of heart sound signals plays an essential role in preventing and diagnosing cardiac diseases. This study proposes a multi-level feature encoding algorithm based on frequency-balanced power spectral intensity for heart sound signal classification. Firstly, a wavelet threshold function is employed to denoise the heart sound signals. Then, th...
The detection of heart disease using a stethoscope requires significant skill and time, making it expensive and impractical for widespread screening in low-resource environments. Machine learning analysis of heart sound recordings can improve upon the accessibility and accuracy of diagnoses, but existing approaches require further validation on lar...
Heart disease continues to be a primary cause of mortality globally, highlighting the critical necessity for efficient early prediction and classification techniques. This study presents a new hybrid model attention‐based CNN‐Bi‐LSTM that integrates the SMOTE with an attention‐driven improved convolutional neural network‐recurrent neural network ar...
Cardiovascular diseases (CVDs) stand as the primary reason of fatalities globally, especially in low-and middle-income countries. In recent years, with the leverage of computer audition technologies, the diagnosis of CVDs through heart sounds become a popular topic. Current models and techniques are trained, validated, and tested on the same datase...
Cardiovascular diseases (CVDs) constitute the primary cause of human mortality globally in recent decades. To effectively detect CVDs, heart auscultation plays an important role in early diagnosis. With the development of artificial intelligence (AI), many studies have designed varying AI-assisted diagnosis systems helping people discriminate abnor...
A pregnant woman was brought to the emergency department looking starved and neglected. She was diagnosed with sepsis and started on intravenous antibiotics. She was also disoriented and hypernatremic. When the fetal heart sounds were found to be absent, the patient was diagnosed with septic miscarriage, which was managed by misoprostol, and after...
Introduction
Application of Deep Learning (DL) methods is being increasingly appreciated by researchers from the biomedical engineering domain in which heart sound analysis is an important topic of study. Diversity in methodology, results, and complexity causes uncertainties in obtaining a realistic picture of the methodological performance from th...
Telemedicine’s rising popularity, driven by its convenience and accessibility, faces a challenge in remote physical auscultation, particularly for assessing lung and heart sounds. We propose a smartphone-based tele-auscultation approach for capturing lung and heart sounds, based on pitch-shifting customized for smartphone listening, overcoming the...
Recently, a new set of biometric traits, called medical biometrics, have been explored for human identity verification. This study introduces a novel framework for recognizing human identity through heart sound signals, commonly referred to as phonocardiograms (PCGs). The framework is built on extracting and suitably processing Mel-Frequency Cepstr...
![Types of heart signals [7].](publication/385610959/figure/fig1/AS:11431281363475238@1744169983011/Types-of-heart-signals-7_Q320.jpg)
![Abnormal PCG (a0006.wav [11]): (a) original file; (b) harmonic and...](publication/385610959/figure/fig4/AS:11431281363761896@1744169985019/Abnormal-PCG-a0006wav-11-a-original-file-b-harmonic-and-percussive-components_Q320.jpg)
![Normal PCG (a0007.wav [11]): (a) original file; (b) harmonic and...](publication/385610959/figure/fig5/AS:11431281363494520@1744169986457/Normal-PCG-a0007wav-11-a-original-file-b-harmonic-and-percussive-components_Q320.jpg)
Cardiovascular diseases (CVDs) are a leading cause of mortality worldwide, with a particularly high burden in India. Non-invasive methods like Phonocardiogram (PCG) analysis capture the acoustic activity of the heart. This holds significant potential for the early detection and diagnosis of heart conditions. However, the complexity and variability...
Background: Having a child with mental ability is very challenging for the mother as the main caregiver.
Objectives: The present study aimed to examine the effectiveness of spiritual counseling based on the sound heart model (SHM) on the resilience and parenting competence of mothers with intellectually disabled children.
Methods: This experimental...
The proposed system consists of a two-stage cascade. The first stage performs a rough heartbeat detection while the second stage refines the previous one, improving the temporal localization and also classifying the heartbeats into types S1 and S2. The first contribution is a novel approach that combines the dissimilarity matrix with the frame-leve...
Non-invasive diagnostic modalities are integral to cardiovascular care; however, current systems primarily measure peripheral pressure, limiting the breadth of cardiovascular prognostication. We report a novel approach for extracting left side heart sounds using a brachial cuff device. The technique leverages brachial cuff device enhanced signal re...
Cardiovascular diseases (CVDs) account for about 32% of global deaths. While digital stethoscopes can record heart sounds, expert analysis is often lacking. To address this, we propose LightCardiacNet, an interpretable, lightweight ensemble neural network using Bi-Directional Gated Recurrent Units (Bi-GRU). It is trained on the PASCAL Heart Challen...
Developing explainable machine intelligence (XAI) models for heart sound abnormality detection is a crucial area of research aimed at improving the interpretability and transparency of machine learning algorithms in medical diagnostics. In this study, we propose a framework for building XAI models that can effectively detect abnormalities in heart...
![(a) The blood flow through the four valves of the heart [37]. (b)...](publication/385483058/figure/fig1/AS:11431281391170691@1745321121284/a-The-blood-flow-through-the-four-valves-of-the-heart-37-b-Normal-phonocardiogram_Q320.jpg)
![(a) Commercial ECM [68]. (b) The general structure of an electret...](publication/385483058/figure/fig5/AS:11431281391295844@1745321125800/a-Commercial-ECM-68-b-The-general-structure-of-an-electret-microphone-65-c_Q320.jpg)
This paper presents a comprehensive review of cardiorespiratory auscultation sensing devices (i.e., stethoscopes), which is useful for understanding the theoretical aspects and practical design notes. In this paper, we first introduce the acoustic properties of the heart and lungs, as well as a brief history of stethoscope evolution. Then, we discu...
Background
Heart failure with preserved ejection fraction (HFpEF) is associated with high hospitalization and mortality rates, representing a significant healthcare burden. This study aims to utilize various information including echocardiogram and phonocardiogram to construct and validate a nomogram, assisting in clinical decision‐making.
Methods...
Background
Human rhinoviruses (HRVs) are among the most common pathogens of upper respiratory infections, and they are responsible for the common cold. An increasing number of studies have shown that HRV is associated with more severe illness. However, HRV-associated fulminant myocarditis has rarely been reported.
Patient presentation
A previously...
Background
A heart positioned on the right side of the thorax can be more a complex situation than it seems, also the potentially associated congenital cardiopathies are variable. In this regard, patients with dextrocardia presenting with complete atrioventricular block require a thorough anatomical investigation to map the veno-arterial system and...
Background :In the field of respiratory system diseases, the utilization of respiratory sounds in auscultation plays a crucial role in the specific disease diagnosis. However, during the process of auscultation, the personal experiences and environmental factors may affect the decision making, leading to diagnostic errors. Therefore, to accurately...
