Cardiac Auscultation: Rediscovering the Lost Art

Cloud-Connected Patch-Worn Auscultation Device for Chest Sound Monitoring

In recent years, wearable electrocardiograms have risen in popularity as a solution for personal monitoring of heart activity. However, this technology has limitations in diagnostic capability and structural function monitoring. Meanwhile, auscultation of the heart remains a fundamental tool for physicians in diagnosis and monitoring of heart disease largely unaddressed in a convenient wearable format. The present work outlines a promising system currently under investigation, allowing user-initiated 10-second chest-sound recordings to be transmitted over Bluetooth-Low-Energy, with an innovative package design providing inherent noise reduction and a high signal-to-noise ratio. The device has been tested on healthy individuals, and system response has been validated against calibrated electrocardiogram recording equipment to analyze signal capture fidelity.

Abstract Figure

Evaluation of a digitally enhanced cardiac auscultation learning method in Cameroon: results of a controlled study

BACKGROUND

Cardiac auscultation is an efficient and effective diagnostic tool, especially in low-income countries where access to modern diagnostic methods remains difficult. This study aimed to evaluate the effect of a digitally enhanced cardiac auscultation learning method on medical students' performance and satisfaction.

METHODS

We conducted a double-arm parallel controlled trial, including newly admitted 4th -year medical students enrolled in two medical schools in Yaoundé, Cameroon and allocated into two groups: the intervention group (benefiting from theoretical lessons, clinical internship and the listening sessions of audio recordings of heart sounds) and the control group (benefiting from theoretical lessons and clinical internship). All the participants were subjected to a pretest before the beginning of the training, evaluating theoretical knowledge and recognition of cardiac sounds, and a post-test at the eighth week of clinical training associated with the evaluation of satisfaction. The endpoints were the progression of knowledge score, skills score, total (knowledge and skills) score and participant satisfaction.

RESULTS

Forty-nine participants (27 in the intervention group and 22 in the control group) completed the study. The knowledge progression (+ 26.7 versus + 7.5; p ˂0.01) and the total progression (+ 22.5 versus + 14.6; p ˂ 0.01) were higher in the intervention group with a statistically significant difference compared to the control group. There was no significant difference between the two groups regarding skills progression (+ 25 versus + 17.5; p = 0.27). Satisfaction was higher in general in the intervention group (p ˂ 0.01), which recommended this method compared to the control group.

CONCLUSION

The learning method of cardiac auscultation reinforced by the listening sessions of audio recordings of heart sounds improves medical students' performances (knowledge and global - knowledge and skills) who find it satisfactory and recommendable.

TRIAL REGISTRATION

This trial has been registered the 29/11/2019 in the Pan African Clinical Trials Registry ( http://www.pactr.org ) under unique identification number PACTR202001504666847 and the protocol has been published in BMC Medical Education.

A low power respiratory sound diagnosis processing unit based on LSTM for wearable health monitoring

Early prevention and detection of respiratory disease have attracted extensive attention due to the significant increase in people with respiratory issues. Restraining the spread and relieving the symptom of this disease is essential. However, the traditional auscultation technique demands a high-level medical skill, and computational respiratory sound analysis approaches have limits in constrained locations. A wearable auscultation device is required to real-time monitor respiratory system health and provides consumers with ease. In this work, we developed a Respiratory Sound Diagnosis Processor Unit (RSDPU) based on Long Short-Term Memory (LSTM). The experiments and analyses were conducted on feature extraction and abnormality diagnosis algorithm of respiratory sound, and Dynamic Normalization Mapping (DNM) was proposed to better utilize quantization bits and lessen overfitting. Furthermore, we developed the hardware implementation of RSDPU including a corrector to filter diagnosis noise. We presented the FPGA prototyping verification and layout of the RSDPU for power and area evaluation. Experimental results demonstrated that RSDPU achieved an abnormality diagnosis accuracy of 81.4 %, an area of 1.57 × 1.76 mm under the SMIC 130 nm process, and power consumption of 381.8 μW, which met the requirements of high accuracy, low power consumption, and small area.

HEAR4Health: a blueprint for making computer audition a staple of modern healthcare

Recent years have seen a rapid increase in digital medicine research in an attempt to transform traditional healthcare systems to their modern, intelligent, and versatile equivalents that are adequately equipped to tackle contemporary challenges. This has led to a wave of applications that utilise AI technologies; first and foremost in the fields of medical imaging, but also in the use of wearables and other intelligent sensors. In comparison, computer audition can be seen to be lagging behind, at least in terms of commercial interest. Yet, audition has long been a staple assistant for medical practitioners, with the stethoscope being the quintessential sign of doctors around the world. Transforming this traditional technology with the use of AI entails a set of unique challenges. We categorise the advances needed in four key pillars: Hear, corresponding to the cornerstone technologies needed to analyse auditory signals in real-life conditions; Earlier, for the advances needed in computational and data efficiency; Attentively, for accounting to individual differences and handling the longitudinal nature of medical data; and, finally, Responsibly, for ensuring compliance to the ethical standards accorded to the field of medicine. Thus, we provide an overview and perspective of HEAR4Health: the sketch of a modern, ubiquitous sensing system that can bring computer audition on par with other AI technologies in the strive for improved healthcare systems.

Chatbot‐mediated learning of cardiac auscultation

Previous research suggested cardiac auscultation is underdeveloped in physicians-in-training. Developing proficiency requires wide exposure to signs, practice and feedback, which may not regularly occur in clinical environments. Our novel pilot study using a mixed-methods approach (n = 9) suggests chatbot-mediated learning of cardiac auscultation is accessible and possesses unique advantages, including immediate feedback, helping in the management of cognitive overload and facilitating deliberate practice.

Augmented detection of septal defects using advanced optical coherence tomography network-processed phonocardiogram

BACKGROUND

Cardiac auscultation is a traditional method that is most frequently used for identifying congenital heart disease (CHD). Failure to diagnose CHD may occur in patients with faint murmurs or obesity. We aimed to develop an intelligent diagnostic method of detecting heart murmurs in patients with ventricular septal defects (VSDs) and atrial septal defects (ASDs).

MATERIALS AND METHODS

Digital recordings of heart sounds and phonocardiograms of 184 participants were obtained. All participants underwent echocardiography by pediatric cardiologists to determine the type of CHD. The phonocardiogram data were classified as normal, ASD, or VSD. Then, the phonocardiogram signal was used to extract features to construct diagnostic models for disease classification using an advanced optical coherence tomography network (AOCT-NET). Cardiologists were asked to distinguish normal heart sounds from ASD/VSD murmurs after listening to the electronic sound recordings. Comparisons of the cardiologists' assessment and AOCT-NET performance were performed.

RESULTS

Echocardiography results revealed 88 healthy participants, 50 with ASDs, and 46 with VSDs. The AOCT-NET had no advantage in detecting VSD compared with cardiologist assessment. However, AOCT-NET performance was better than that of cardiologists in detecting ASD (sensitivity, 76.4 vs. 27.8%, respectively; specificity, 90 vs. 98.5%, respectively).

CONCLUSION

The proposed method has the potential to improve the ASD detection rate and could be an important screening tool for patients without symptoms.

Novice Accuracy in Ultrasound and Stethoscope Study (NAUSS)

INTRODUCTION

The purpose of this noninferiority study was the accurate determination of valvular heart disease, using bedside echocardiogram as compared to stethoscope, by a novice clinician examiner.

METHODS

We conducted a single university, single program study to investigate the use of bedside ultrasound in the hands of a novice clinical user, defined as someone with fewer than 2 years of clinical education. We enrolled 8 examinees with evidence of valvular heart disease to be assessed by 13 subjects.

RESULTS

Descriptive statistics revealed echocardiogram accuracy of 56% compared to 44% accuracy with stethoscope, though not statistically significant. Interestingly, 31% of subjects obtained equal measures with both instruments. Correlation proficiency between both modalities was also observed.

DISCUSSION

There is no statistically significant difference in novice examiner diagnostic accuracy using point-of-care echocardiograms for examination of valvular heart disease when compared with a stethoscope.

Classification of Children's Heart Sounds With Noise Reduction Based on Variational Modal Decomposition

Purpose

Children's heart sounds were denoised to improve the performance of the intelligent diagnosis.

Methods

A combined noise reduction method based on variational modal decomposition (VMD) and wavelet soft threshold algorithm (WST) was proposed, and used to denoise 103 phonocardiogram samples. Features were extracted after denoising and employed for an intelligent diagnosis model to verify the effect of the denoising method.

Results

The noise in children's phonocardiograms, especially crying noise, was suppressed. The signal-to-noise ratio obtained by the method for normal heart sounds was 14.69 dB at 5 dB Gaussian noise, which was higher than that obtained by WST only and the other VMD denoising method. Intelligent classification showed that the accuracy, sensitivity and specificity of the classification system for congenital heart diseases were 92.23, 92.42, and 91.89%, respectively and better than those with WST only.

Conclusion

The proposed noise reduction method effectively eliminates noise in children's phonocardiograms and improves the performance of intelligent screening for the children with congenital heart diseases.

Mitral Valve Regurgitation Murmurs—Insights from Hemoacoustic Computational Modeling

Mitral regurgitation (MR) is the leakage of blood from the left ventricle into the left atrium during systole through a mitral valve that does not close fully. A systolic murmur is produced by MR and can be used to diagnose this disease. In the current study, we use hemoacoustic simulations to characterize the features of murmurs for a range of severities relevant to chronic MR. The incompressible Navier–Stokes equations are solved using an immersed boundary method to simulate the blood flow. The resultant pressure fluctuations on the lumen wall serve as the source for the murmur, and the murmur propagation through the thorax is modeled as a 3D elastic wave in a linear viscoelastic material. The resulting acceleration on the surface of the thorax is used as a surrogate for the measurement from a stethoscope, and these characteristics of the acceleration signal are examined in detail. We found that the intensity of the MR murmur is lower at the mitral point on the precordium, as compared with the aortic and pulmonic areas. This is somewhat counterintuitive but is supported by other studies in the past. We also found that the intensity of the murmur, as well as the break frequency, are well correlated with the severity of MR, and this information can be useful for automated auscultation and phonocardiographic applications.

Virtual auscultation course via video chat in times of COVID-19 improves cardiac auscultation skills compared to literature self-study in third-year medical students: a prospective randomized controlled cross-over study

BACKGROUND

Cardiac auscultation is a core clinical skill taught in medical school. Due to contact restrictions during the SARS-CoV-2 pandemic, interaction with patients was very limited. Therefore, a peer-to-peer virtual case-based auscultation course via video conference was established.

METHODS

A randomized controlled cross-over study was conducted to evaluate whether participation in a virtual auscultation course could improve heart auscultation skills in 3^rd-year medical students. A total of sixty medical students were randomly assigned to either the experimental or control group after informed consent was obtained. Due to no-shows, 55 students participated. Depending on allocation, students attended three ninety-minute courses in intervals of one week in a different order: a virtual case-based auscultation course held via video chat, literature self-study, and an on-site course using a high-fidelity auscultation simulator (SAM II). The study's primary endpoint was the performance of the two groups at the simulator after participating in the virtual auscultation course or literature self-study. To evaluate their auscultation skills, students participated in five assessments using the same six pathologies: stenosis and regurgitation of the aortic and mitral valve, ventricular septal defect, and patent ductus arteriosus. Moreover, participants rated their satisfaction with each course and provided a self-assessment of competence.

RESULTS

Compared to literature self-study, participation in the virtual auscultation course led to a significantly improved description of heart murmurs at the auscultation simulator with regard to the presence in systole and diastole, low- and high-pitched sounds, and volume dynamics. There was no significant difference between the groups in diagnostic accuracy and identification of the point of maximal intensity. After the virtual course, students showed higher satisfaction rates and a higher increase in self-assessed competence compared to participants who engaged in literature self-study.

CONCLUSIONS

For the first time, this study demonstrates that a case-based virtual auscultation course can improve aspects of cardiac auscultation skills on a simulator. This may facilitate the further acquisition of an essential clinical skill, even when contact restrictions will be lifted.

Deep Learning Algorithm for Heart Valve Diseases Assisted Diagnosis

Heart sounds are mainly the expressions of the opening and closing of the heart valves. Some sounds are produced by the interruption of laminar blood flow as it turns into turbulent flow, which is explained by abnormal functioning of the valves. The analysis of the phonocardiographic signals has made it possible to indicate that the normal and pathological records differ from each other concerning both temporal and spectral features. The present work describes the design and implementation based on deep neural networks and deep learning for the binary and multiclass classification of four common valvular pathologies and normal heart sounds. For feature extraction, three different techniques were considered: Discrete Wavelet Transform, Continuous Wavelet Transform and Mel Frequency Cepstral Coefficients. The performance of both approaches reached F1 scores higher than 98% and specificities in the “Normal” class of up to 99%, which considers the cases that can be misclassified as normal. These results place the present work as a highly competitive proposal for the generation of systems for assisted diagnosis.

The CirCor DigiScope Dataset: From Murmur Detection to Murmur Classification

Cardiac auscultation is one of the most cost-effective techniques used to detect and identify many heart conditions. Computer-assisted decision systems based on auscultation can support physicians in their decisions. Unfortunately, the application of such systems in clinical trials is still minimal since most of them only aim to detect the presence of extra or abnormal waves in the phonocardiogram signal, i.e., only a binary ground truth variable (normal vs abnormal) is provided. This is mainly due to the lack of large publicly available datasets, where a more detailed description of such abnormal waves (e.g., cardiac murmurs) exists. To pave the way to more effective research on healthcare recommendation systems based on auscultation, our team has prepared the currently largest pediatric heart sound dataset. A total of 5282 recordings have been collected from the four main auscultation locations of 1568 patients, in the process, 215780 heart sounds have been manually annotated. Furthermore, and for the first time, each cardiac murmur has been manually annotated by an expert annotator according to its timing, shape, pitch, grading, and quality. In addition, the auscultation locations where the murmur is present were identified as well as the auscultation location where the murmur is detected more intensively. Such detailed description for a relatively large number of heart sounds may pave the way for new machine learning algorithms with a real-world application for the detection and analysis of murmur waves for diagnostic purposes.

A novel multi-branch architecture for state of the art robust detection of pathological phonocardiograms

Heart auscultation is an inexpensive and fundamental technique to effectively diagnose cardiovascular disease. However, due to relatively high human error rates even when auscultation is performed by an experienced physician, and due to the not universal availability of qualified personnel, e.g. in developing countries, many efforts are made worldwide to propose computational tools for detecting abnormalities in heart sounds. The large heterogeneity of achievable data quality and devices, the variety of possible heart pathologies, and a generally poor signal-to-noise ratio make this problem very challenging. We present an accurate classification strategy for diagnosing heart sounds based on (1) automatic heart phase segmentation, (2) state-of-the art filters drawn from the field of speech synthesis (mel-frequency cepstral representation) and (3) an ad hoc multi-branch, multi-instance artificial neural network based on convolutional layers and fully connected neuronal ensembles which separately learns from each heart phase hence implicitly leveraging their different physiological significance. We demonstrate that it is possible to train our architecture to reach very high performances, e.g. an area under the curve of 0.87 or a sensitivity of 0.97. Our machine-learning-based tool could be employed for heartsound classification, especially as a screening tool in a variety of situations including telemedicine applications. This article is part of the theme issue 'Advanced computation in cardiovascular physiology: new challenges and opportunities'.

Advances in Microsensors and Wearable Bioelectronics for Digital Stethoscopes in Health Monitoring and Disease Diagnosis

Acoustic stethoscopes have demonstrated beneficial factors aiding diagnosis from the doctors with accurate body sounds. Still, the conventional acoustic stethoscopes require a substantial amount of clinical experience and hearing skills for the physicians to accurately diagnose symptoms from abnormal sounds. Especially for cardiopulmonary systems, it is crucial to collect sounds with precision since they contain valuable information in specific frequency ranges for various sounds. This review paper summarizes recent advances and technical developments in microsensors, circuits, chips, and integrated electronics for fabricating different digital stethoscopes that offer portable detection of body sounds. They solve the limitations of conventional stethoscopes, aiming for wireless auscultation in digitized medicine. Overall, this comprehensive review will help researchers design and develop new wearable electronics and digital stethoscopes for advancing human healthcare, continuous monitoring, and better diagnosis.

Evaluation of a digitally enhanced cardiac auscultation learning method: a controlled study

BACKGROUND

Cardiac auscultation remains an efficient and accessible diagnostic tool, especially in resource-limited countries where modern diagnostic devices like cardiac ultrasound are expensive and difficult to access. However, cardiac auscultation skills of medical students and physicians are declining, mainly because of an ineffective teaching method for this technique. The objective of this study is to evaluate the effect of a digitally enhanced cardiac auscultation learning method on participants' theoretical knowledge and auscultation skills.

METHODS

This will be a controlled study with two parallel arms (1:1). Participants (fourth-year medical students) will be divided into two groups: an intervention group (receiving additional lectures, clinical internship and audio listening sessions) and a control group (receiving additional lectures and clinical internship). At the beginning of the study, all participants will undergo a pre-test that consist of two parts: a knowledge assessment based on multiple-choice questions and a skills assessment based on recognition of cardiac sounds from audio files. Thereafter, three specific additional lectures on cardiac auscultation will be delivered and all participants will take part in their official clinical internship. During these clinical internships (eight weeks), participants of the intervention group will be invited to two listening sessions based on five digital recordings of heart sounds. At the end of the clinical internship, all participants will be invited to a post-test to evaluate their knowledge, skills and satisfaction according to their learning method. The main outcome will be the participants' knowledge progression. The other outcomes will be the participants' skills progression, participants' total progression and satisfaction. Data will be collected and analyzed in per protocol.

DISCUSSION

This study could contribute to the development of a learning method that takes into account the advantages of the conventional method and the contribution of digital technology. Positive results could lead to improved cardiac auscultation skills among health professionals, especially in developing countries.

TRIAL REGISTRATION

The trial is registered on the Pan-African Clinical Trials Registry ( http://www.pactr.org ) under unique identification number: PACTR202001504666847 , registered the 29 November 2019.

Automatic recognition of murmurs of ventricular septal defect using convolutional recurrent neural networks with temporal attentive pooling

Recognizing specific heart sound patterns is important for the diagnosis of structural heart diseases. However, the correct recognition of heart murmur depends largely on clinical experience. Accurately identifying abnormal heart sound patterns is challenging for young and inexperienced clinicians. This study is aimed at the development of a novel algorithm that can automatically recognize systolic murmurs in patients with ventricular septal defects (VSDs). Heart sounds from 51 subjects with VSDs and 25 subjects without a significant heart malformation were obtained in this study. Subsequently, the soundtracks were divided into different training and testing sets to establish the recognition system and evaluate the performance. The automatic murmur recognition system was based on a novel temporal attentive pooling-convolutional recurrent neural network (TAP-CRNN) model. On analyzing the performance using the test data that comprised 178 VSD heart sounds and 60 normal heart sounds, a sensitivity rate of 96.0% was obtained along with a specificity of 96.7%. When analyzing the heart sounds recorded in the second aortic and tricuspid areas, both the sensitivity and specificity were 100%. We demonstrated that the proposed TAP-CRNN system can accurately recognize the systolic murmurs of VSD patients, showing promising potential for the development of software for classifying the heart murmurs of several other structural heart diseases.

Virtual auscultation course for medical students via video chat in times of COVID-19

Introduction: Auscultation skills are among the basic techniques to be learned in medical school. Such skills are achieved through supervised examination of patients often supported by simulator-based learning. The emergence of COVID-19 has disrupted and continues to hinder hands-on on-site medical training on a global scale. Project description: An effective virtual auscultation course was established in times of contact restrictions due to COVID-19 at the Medical Faculty of the Heinrich Heine University Düsseldorf. The interactive case-based webinar was designed to improve listening techniques, description and interpretation of auscultation findings in an off-site context. Clinical cases with pre-recorded auscultation sounds and additional case-based diagnostics were presented. The course focused on common heart murmurs including aortic and mitral valve stenosis and regurgitation as well as congenital heart defects (ventricular septal defect and patent ductus arteriosus). Results: The course was well received by the students and assessed as being useful and instructive. Assessment of learning effects, such as detection of pathological findings before and after training, is ongoing as part of a subsequent trial. Conclusion: Virtual interactive learning using a sound simulation lesson with clinical case presentations via video chat can well be used as a supplement to practical auscultation training. This learning format could also play a useful role in the curriculum of medical studies once contact restrictions are revoked.

The Birth, Death, and Renaissance (?) of Dissection: A Critique of Anatomy Teaching With-or Without-the Human Body

A riveting debate regarding the fate of dissection, the classical method of anatomy, is sweeping through medical academia, as imaging tools gain a greater foothold in anatomy teaching programs. This Perspective does not aim to grapple with the question of "how should anatomy be taught" but rather to explain why the transformation of anatomical education is taking place by situating these developments in the broader philosophical context of modern medicine, offered by Michel Foucault's The Birth of the Clinic: An Archaeology of Medical Perception. Emphasizing the body's crucial role in the epistemological change in medical practice in the early 19th century, Foucault coined the term "medical gaze" to denote the doctor's observation of the patient's body in search of signs of disease. Within this new systematic perception of disease, which brought about the anatomo-clinical method, the clinical gaze thus embraced the study of the body via dissection. The author contends that the introduction of medical imaging into the diagnostic process has resulted in a shift in the focus of the clinical gaze from the body to its medical image and that this process is mirrored in anatomy by its discarding of the cadaver. Given the fundamental differences between the phenomenology of the body and its medical image, the author suggests that when using medical images in medical schools and teaching hospitals, one teaches, at the very least, a new kind of anatomy. Foucault's analysis of the painting The Treachery of Images by Réne Magritte lends some support to the ideas presented here.

Cardiac auscultation skills among junior doctors: effects of sound simulation lesson

OBJECTIVES

To evaluate the effect of a sound simulation lesson to improve cardiac auscultation skills among junior doctors.

METHODS

This study is based on the design of test comparison before and after educational intervention using a convenient sample. For 50 junior doctors in Japan, diagnostic accuracy before and after a sound simulation lesson for cardiac auscultation skills was compared. There were 15 doctors who experienced cardiology rotation. The lesson used seven abnormal cardiac recordings (third heart sound, double gallop, aortic stenosis, aortic regurgitation, mitral stenosis, mitral regurgitation, and pericardial friction rub). At tests before and after the lesson, the doctors listened to random sound outputs of the same seven recordings, chose diagnostic findings from multiple-choice items, and obtained individual diagnostic accuracy based on the total number of choosing correct findings. Top 10 doctors obtaining the greatest individual accuracy received a commendation.

RESULTS

Pre-lesson diagnostic accuracy was not different between doctors with cardiology rotation training (total diagnostic accuracy of the group, 27/105 [26%]) and those without cardiology rotation (70/245 [29%]). Compared to pre-lesson, post-lesson total diagnostic accuracy significantly improved with about two-folds (97/350 [28%] vs 170/350 [61%]; McNemar Test, p<0.0001). The improvement was significant for double gallop (5/50 [10%] vs. 15/50 [30%]), mitral stenosis (0/50 [0%] vs. 6/50 [12%]), and pericardial friction rub (1/50 [2%] vs. 35/50 [70%]).

CONCLUSIONS

The use of a simple sound simulation lesson may help junior doctors to learn cardiac auscultation skills. Clinician educators are encouraged to use this strategy in addition to cardiology rotation training.

Improved Segmentation with Dynamic Threshold Adjustment for Phonocardiography Recordings

In this study with the intent to segment phonocardiography (PCG) recordings, an algorithm that processes a feature vector obtained by jointly using wavelet transform and mel scaled energy spectrum of the PCG signal is proposed. The feature vector is processed by a peak detection algorithm which results in a set of peaks that meet some certain criteria and will be exploited in the succeeding stages of the algorithm. Heart sounds are labeled by convolving circularly a template and a fragment of the feature vector which is picked up with the guidance of the peaks. At the final stage, the algorithm tries to detect and correct erroneous labels. The performance of the algorithm was tested on both normal heart sounds and abnormal heart sounds; 80 records in total. As a result of these tests, for normal heart sounds S1 and S2 sounds were detected with 99,51% recall and 97,28% precision, while with 97,59% recall and 92,53% precision for abnormal heart sounds.

Reliability of focused cardiac ultrasound performed by first-year internal medicine residents at a community hospital after a short training

The use of bedside ultrasound over the past few decades has created a new wave of options for visualizing pathological processes allowing for faster and better detection of disease. We aimed to evaluate the reliability of focused cardiac ultrasound (FCU) performed by first-year internal medicine residents at a community hospital after a short period of training. They received a two-hour lecture and initially performed a supervised FCU followed by ten unsupervised/independent FCUs each. The four parameters that were assessed were left systolic ventricular function, right systolic ventricular function, presence of pericardial effusion, and presence of IVC dilation. Interpretation and analysis of ultrasound images were then carried out by both the residents and an attending physician with expertise in FCU analysis and interpretation. Cohen's Kappa values were obtained comparing the results found by the interns versus the attending. Our findings indicate that more training is required for reliable analysis of FCU by first-year medical residents. Our results also emphasize the need to carefully evaluate the medical residents' FCU skills after the training.

Aortic valve stenosis awareness in Austria-results of a nationwide survey in 1001 subjects

Despite the prognostic significance of severe aortic valve stenosis, knowledge is limited in the general population. To document the status quo for Austria, knowledge about valvular heart disease/aortic valve stenosis was documented in 1001 participants >60 years of age. 6.7% of respondents were knowledgeable of aortic valve stenosis, with 1.6% being concerned about the condition (24.1% cancer, 18.8% Alzheimer’s disease, 15.1% stroke). 29.5% were familiar with valvular heart disease (76.7% heart attack, 36.9% stroke). Only 1/3 reported auscultation by their general practitioner (GP) at least every third visit. Typical symptoms of aortic valve stenosis were likely to be reported by 50%. After exposure to further information on aortic valve stenosis, only 20% reported to be more concerned and ready to obtain more disease-related information. Awareness of surgical and catheter-based treatment options was claimed by 77% of respondents. Awareness campaigns on valvular heart disease are warranted to improve patient care in Austria.

A prospective study on the efficacy of patient simulation in heart and lung auscultation

BACKGROUND

The use of simulation technology for skill training and assessment in medical education has progressively increased over the last decade. Nevertheless, the teaching efficacy of most technologies remains to be fully determined. The aim of this prospective study was to evaluate if a short individual training on a patient simulator could improve heart and lung auscultation skills in undergraduate students.

METHODS

A group of fifth-year medical school students, who had trained on a patient simulator in their third year (EXP, n = 55), was compared to a group of fifth-year medical school students who had not previously trained on it (CNT, n = 49). Students were recruited on a voluntary basis. Students were evaluated in terms of their ability to correctly identify three heart (II sound wide split, mitral regurgitation, aortic stenosis) and five lung sounds (coarse crackles, fine crackles, pleural rubs, rhonchi, wheezes), which were reproduced in a random order on the Kyoto-Kagaku patient simulator.

RESULTS

Exposure to patient simulator significantly improved heart auscultation skills, as mitral regurgitation was correctly recognized by 89.7% of EXP students as compared to 71.4% of CNT students (p = 0.02). In addition, a significantly greater percentage of EXP students correctly graphed all the heart diagnoses as compared to CNT students. There were no differences between the groups in lung auscultation.

CONCLUSIONS

This study demonstrates that training medical students with a patient simulator, individually for one hour, significantly ameliorated their heart auscultation skills. Our data suggests that patient simulation might be useful for learning auscultation skills, especially when it is combined with graphic sound display.

Patient screening for early detection of aortic stenosis (AS)-review of current practice and future perspectives

In Europe, approximately one million people over 75 years suffer from severe aortic stenosis (AS), one of the most serious and most common valve diseases, and this disease burden is increasing with the aging population. A diagnosis of severe symptomatic AS is associated with an average life expectancy of 2-3 years and necessitates a timely valve intervention. Guidelines for valve replacement therapy have been established but only a proportion of patients with symptomatic AS actually receive this life-saving treatment. The decision for valve intervention in asymptomatic patients with severe AS is often more challenging and likely results in fewer patients receiving treatment in comparison to their symptomatic counterparts. This article reviews the epidemiology and clinical manifestations of AS, the associated economic burden of AS to the healthcare system, the diagnosis of AS and the possible mechanisms for the introduction of routine screening in elderly patients. Elderly patients typically visit healthcare providers more frequently than younger patients, thereby providing increased opportunities for ad hoc AS screening and this, along with raising patient awareness of the symptoms of AS, has the potential to result in the earlier diagnosis and treatment of AS and increased patient survival.

Novel algorithm to screen for heart murmurs using computer-aided auscultation in neonates: a prospective single center pilot observational study

BACKGROUND

Automated detection of heart murmurs with computer-aided auscultation is not yet in clinical routine use. Aim of this study was to test sensitivity and specificity of a novel prototype algorithm in automated detection of heart murmurs from digitally recorded phonocardiograms in neonates admitted at the Neonatal Intensive Care Unit.

METHODS

In a prospective pilot observational study from November 2012 to December 2013 auscultations by pediatricians and computer aided auscultation were performed within 12 hours of neonatal echocardiography. Echocardiography was defined as pathological when resulting in any clinical consequences or causing murmur. Phonocardiograms and auscultation were defined as pathological if a murmur was detected. Phonocardiograms were analyzed offline with a novel algorithm prototype (CSD Labs, Graz, Austria) for detection of murmurs in neonates in a first run and with an optimized algorithm in a second run and were compared with echocardiography. Sensitivity and specificity of auscultation by pediatrician and computer aided auscultation were analyzed.

RESULTS

Thirty-six neonates (gestational age: 36±3 weeks) were included. Twenty-three (64%) neonates had pathological or murmur causing findings in echocardiography (positive echocardiography). Sensitivity and specificity of auscultation by pediatrician were 17% and 100%, respectively. In comparison to auscultation by pediatrician sensitivity of first run and second run were significantly higher with 70% and 83%, respectively. Specificity of first run and second run were 77% and 85%, respectively.

CONCLUSIONS

Phonocardiogram analysis using the novel algorithm prototype had a higher sensitivity than auscultation by pediatrician in detecting positive echocardiography findings in neonates.

A New Stethoscope Design with Unique Characteristics and Development in Medical Device

As regards the significant role of stethoscopes in the diagnosis of congenital and adventitious heart diseases and prevention of irreparable complications of these diseases, the quality of hearing sound of these stethoscopes by a physician has a significant impact on the disease diagnosis. This device plays an important role in the early diagnosis of congenital heart and respiratory diseases and provides this feasibility since birth. Also, the importance of this device performance in the diagnosis of heart, cardiovascular and respiratory diseases at different age periods is not a secret. This new invented device, in comparison to a variety of available stethoscopes in the field of diagnosis, is capable of hearing the sound of a very high quality and cancelling the noise of sound that sometimes leads to wrong diagnosis or misdiagnosis. This new invented stethoscope is approved by cardiologists, lung and Infectious disease specialists as well as being registered under No. 78382 in Patent Islamic Republic of Iran.

Cardiac Auscultation for Noncardiologists: Application in Cardiac Rehabilitation Programs: PART II: ADULT PATIENTS AFTER HEART SURGERY

This clinical skills review describes the most common cardiac auscultatory findings in adults after heart surgery and correlates them with prognostic indicators. It was written for noncardiologist health care providers who work in outpatient cardiac rehabilitation programs.Mechanical prosthetic valves produce typical closing and opening clicks. Listening to their timing and features, as well as to presence and quality of murmurs, contributes to the awareness of potential prosthesis malfunction before other dramatic clinical signs or symptoms become evident. In patients with biological prostheses, murmurs should be carefully evaluated to rule out both valve malfunction and degeneration. Rubs of post-pericardiotomy pericarditis should prompt further investigation for early signs of cardiac tamponade. Third and fourth heart sounds and systolic murmurs in anemic patients should be differentiated from pathological conditions. Relatively new groups of heart surgery patients are those with chronic heart failure treated with continuous-flow left ventricle assist devices. These devices produce characteristic continuous noise that may suddenly disappear or vary in quality and intensity with device malfunction. After heart transplantation, a carefully performed and regularly repeated cardiac auscultation may contribute to suspicion of impending acute rejection. During cardiac rehabilitation, periodic cardiac auscultation may provide useful information regarding clinical-hemodynamic status and allow detection of heralding signs of possible complications in an efficient and low-cost manner.

Cardiac Auscultation for Noncardiologists: Application in Cardiac Rehabilitation Programs: PART I: PATIENTS AFTER ACUTE CORONARY SYNDROMES AND HEART FAILURE

During outpatient cardiac rehabilitation after an acute coronary syndrome or after an episode of congestive heart failure, a careful, periodic evaluation of patients' clinical and hemodynamic status is essential. Simple and traditional cardiac auscultation could play a role in providing useful prognostic information.Reduced intensity of the first heart sound (S1), especially when associated with prolonged apical impulse and the appearance of added sounds, may help identify left ventricular (LV) dysfunction or conduction disturbances, sometimes associated with transient myocardial ischemia. If both S1 and second heart sound (S2) are reduced in intensity, a pericardial effusion may be suspected, whereas an increased intensity of S2 may indicate increased pulmonary artery pressure. The persistence of a protodiastolic sound (S3) after an acute coronary syndrome is an indicator of severe LV dysfunction and a poor prognosis. In patients with congestive heart failure, the association of an S3 and elevated heart rate may indicate impending decompensation. A presystolic sound (S4) is often associated with S3 in patients with LV failure, although it could also be present in hypertensive patients and in patients with an LV aneurysm. Careful evaluation of apical systolic murmurs could help identifying possible LV dysfunction or mitral valve pathology, and differentiate them from a ruptured papillary muscle or ventricular septal rupture. Friction rubs after an acute myocardial infarction, due to reactive pericarditis or Dressler syndrome, are often associated with a complicated clinical course.During cardiac rehabilitation, periodic cardiac auscultation may provide useful information about the clinical-hemodynamic status of patients and allow timely detection of signs, heralding possible complications in an efficient and low-cost manner.

Development of a Smartphone App for Visualizing Heart Sounds and Murmurs

BACKGROUND

Auscultation is one of the basic techniques for the diagnosis of heart disease. However, the interpretation of heart sounds and murmurs is a highly subjective and difficult skill.

OBJECTIVES

To assist the auscultation skill at the bedside, a handy phonocardiogram was developed using a smartphone (Samsung Galaxy J, Android OS 4.4.2) and an external microphone attached to a stethoscope.

METHODS AND RESULTS

The Android app used Java classes, "AudioRecord," "AudioTrack," and "View," that recorded sounds, replayed sounds, and plotted sound waves, respectively. Sound waves were visualized in real-time, simultaneously replayed on the smartphone, and saved to WAV files. To confirm the availability of the app, 26 kinds of heart sounds and murmurs sounded on a human patient simulator were recorded using three different methods: a bell-type stethoscope, a diaphragm-type stethoscope, and a direct external microphone without a stethoscope. The recorded waveforms were subjectively confirmed and were found to be similar to the reference waveforms.

CONCLUSIONS

The real-time visualization of the sound waves on the smartphone may help novices to readily recognize and learn to distinguish the various heart sounds and murmurs in real-time.

Initial Field Test of a Cloud-Based Cardiac Auscultation System to Determine Murmur Etiology in Rural China

A system for collection, distribution, and long distant, asynchronous interpretation of cardiac auscultation has been developed and field-tested in rural China. We initiated a proof-of-concept test as a critical component of design of a system to allow rural physicians with little experience in evaluation of congenital heart disease (CHD) to obtain assistance in diagnosis and management of children with significant heart disease. The project tested the hypothesis that acceptable screening of heart murmurs could be accomplished using a digital stethoscope and internet cloud transmittal to deliver phonocardiograms to an experienced observer. Of the 7993 children who underwent school-based screening in the Menghai District of Yunnan Province, Peoples Republic of China, 149 had a murmur noted by a screener. They had digital heart sounds and phonocardiograms collected with the HeartLink tele auscultation system, and underwent echocardiography by a cardiology resident from the First Affiliated Hospital of Kunming Medical University. The digital phonocardiograms, stored on a cloud server, were later remotely reviewed by a board-certified American pediatric cardiologist. Fourteen of these subjects were found to have CHD confirmed by echocardiogram. Using the HeartLink system, the pediatric cardiologist identified 11 of the 14 subjects with pathological murmurs, and missed three subjects with atrial septal defects, which were incorrectly identified as venous hum or Still's murmur. In addition, ten subjects were recorded as having pathological murmurs, when no CHD was confirmed by echocardiography during the field study. The overall test accuracy was 91% with 78.5% sensitivity and 92.6% specificity. This proof-of-concept study demonstrated the feasibility of differentiating pathologic murmurs due to CHD from normal functional heart murmurs with the HeartLink system. This field study is an initial step to develop a cost-effective CHD screening strategy in low-resource settings with a shortage of trained medical professionals and pediatric heart programs.

The Diagnostic Utility of Computer-Assisted Auscultation for the Early Detection of Cardiac Murmurs of Structural Origin in the Periodic Health Evaluation

BACKGROUND

Identification of the nature of cardiac murmurs during the periodic health evaluation (PHE) of athletes is challenging due to the difficulty in distinguishing between murmurs of physiological or structural origin. Previously, computer-assisted auscultation (CAA) has shown promise to support appropriate referrals in the nonathlete pediatric population.

HYPOTHESIS

CAA has the ability to accurately detect cardiac murmurs of structural origin during a PHE in collegiate athletes.

STUDY DESIGN

Cross-sectional, descriptive study.

LEVEL OF EVIDENCE

Level 3.

METHODS

A total of 131 collegiate athletes (104 men, 28 women; mean age, 20 ± 2 years) completed a sports physician (SP)-driven PHE consisting of a cardiac history questionnaire and a physical examination. An independent CAA assessment was performed by a technician who was blinded to the SP findings. Athletes with suspected structural murmurs or other clinical reasons for concern were referred to a cardiologist for confirmatory echocardiography (EC).

RESULTS

Twenty-five athletes were referred for further investigation (17 murmurs, 6 abnormal electrocardiographs, 1 displaced apex, and 1 possible case of Marfan syndrome). EC confirmed 3 structural and 22 physiological murmurs. The SP flagged 5 individuals with possible underlying structural pathology; 2 of these murmurs were confirmed as structural in nature. Fourteen murmurs were referred by CAA; 3 of these were confirmed as structural in origin by EC. One such murmur was not detected by the SP, however, and detected by CAA. The sensitivity of CAA was 100% compared with 66.7% shown by the SP, while specificity was 50% and 66.7%, respectively.

CONCLUSION

CAA shows potential to be a feasible adjunct for improving the identification of structural murmurs in the athlete population. Over-referral by CAA for EC requires further investigation and possible refinements to the current algorithm. Further studies are needed to determine the true sensitivity, specificity, and cost efficacy of the device among the athletic population.

CLINICAL RELEVANCE

CAA may be a useful cardiac screening adjunct during the PHE of athletes, particularly as it may guide appropriate referral of suspected structural murmurs for further investigation.

Auscultation of the heart: The Basics with Anatomical Correlation

Proficiency in heart auscultation continues to be important even in an era of modern technology. However, many physicians and health care providers are uncomfortable and often inaccurate in their ability to identify normal and abnormal heart sounds. The following review was performed to provide a basis that health care providers can use to strengthen their understanding and improve their techniques when auscultating the human heart. Clin. Anat. 30:58-60, 2017. © 2016 Wiley Periodicals, Inc.

The 200th anniversary of the stethoscope: Can this low-tech device survive in the high-tech 21st century?

In 1816, Laennec discovered that auscultation of the heart and lungs could effectively be performed by placing a hollow cylinder (initially made of a roll of paper) between the chest of the patient and the ear of the examiner. This was the first step in the development of the stethoscope, which was a breakthrough in the diagnosis and management of cardiac and pulmonary patients. Technical improvements of the stethoscope followed and in cardiac patients auscultation soon became a major diagnostic tool. In the second half of the 20th century, new powerful non-invasive diagnostic modalities were developed and the interest in auscultation declined. As a result, the auscultatory skills of students and physicians at all levels of training decreased to a disappointingly low level. We now must decide whether we should stimulate the use of and proficiency in auscultation or if we should accept the further decline and eventual abolishment of this component of the physical examination. Reviewing the literature and taking into consideration the setting in which the patients are presented, including the availability of advanced diagnostic facilities, we conclude that the time-honoured stethoscope, in spite of its limitations, still has potential as a patient-friendly, effective, and economical instrument in medical practice. However, new initiatives are required to train students, physicians and allied health professionals in cardiac auscultation to avoid misinterpretations that may harm the patients and generate extra costs. To be successful such programs will require wide support from the medical community.

Auscultating heart and breath sounds through patients' gowns: who does this and does it matter?

BACKGROUND

Doctors are taught to auscultate with the stethoscope applied to the skin, but in practice may be seen applying the stethoscope to the gown.

OBJECTIVES

To determine how often doctors auscultate heart and breath sounds through patients' gowns, and to assess the impact of this approach on the quality of the sounds heard.

METHODS

A sample of doctors in the west of Scotland were sent an email in 2014 inviting them to answer an anonymous questionnaire about how they auscultated heart and breath sounds. Normal heart sounds from two subjects were recorded through skin, through skin and gown, and through skin, gown and dressing gown. These were played to doctors, unaware of the origin of each recording, who completed a questionnaire about the method and quality of the sounds they heard.

RESULTS

206 of 445 (46%) doctors completed the questionnaire. 124 (60%) stated that they listened to patients' heart sounds, and 156 (76%) to patients' breath sounds, through patients' gowns. Trainees were more likely to do this compared with consultants (OR 3.39, 95% CI 1.74 to 6.65). Doctors of all grades considered this practice affected the quality of the sounds heard. 32 doctors listened to the recorded heart sounds. 23 of the 64 (36%) skin and 23 of the 64 (36%) gown recordings were identified. The majority of doctors (74%) could not differentiate between skin or gown recordings, but could tell them apart from the double layer recordings (p=0.02). Trainees were more likely to hear artefactual added sounds (p=0.04).

CONCLUSIONS

Many doctors listen to patients' heart and breath sounds through hospital gowns, at least occasionally. In a short test, most doctors could not distinguish between sounds heard through a gown or skin. Further work is needed to determine the impact of this approach to auscultation on the identification of murmurs and added sounds.

Quantitative Measurement of Split of the Second Heart Sound (S2)

This study proposes a quantitative measurement of split of the second heart sound (S2) based on nonstationary signal decomposition to deal with overlaps and energy modeling of the subcomponents of S2. The second heart sound includes aortic (A2) and pulmonic (P2) closure sounds. However, the split detection is obscured due to A2-P2 overlap and low energy of P2. To identify such split, HVD method is used to decompose the S2 into a number of components while preserving the phase information. Further, A2s and P2s are localized using smoothed pseudo Wigner-Ville distribution followed by reassignment method. Finally, the split is calculated by taking the differences between the means of time indices of A2s and P2s. Experiments on total 33 clips of S2 signals are performed for evaluation of the method. The mean ± standard deviation of the split is 34.7 ± 4.6 ms. The method measures the split efficiently, even when A2-P2 overlap is ≤ 20 ms and the normalized peak temporal ratio of P2 to A2 is low (≥ 0.22). This proposed method thus, demonstrates its robustness by defining split detectability (SDT), the split detection aptness through detecting P2s, by measuring up to 96 percent. Such findings reveal the effectiveness of the method as competent against the other baselines, especially for A2-P2 overlaps and low energy P2.

Effects of ultrasound implementation on physical examination learning and teaching during the first year of medical education

OBJECTIVES

Increasing emphasis has been placed on point-of-care ultrasound in medical school. The overall effects of ultrasound curriculum implementation on the traditional physical examination skills of medical students are still unknown. We studied the effects on the Objective Standardized Clinical Examination (OSCE) scores of year 1 medical students before and after ultrasound curriculum implementation.

METHODS

An ultrasound curriculum was incorporated into the physical diagnosis course for year 1 medical students in the 2012-2013 academic year. We performed a prospective observational study comparing traditional OSCE scores of year 1 medical students exposed to the ultrasound curriculum (post-ultrasound) versus historic year 1 medical student controls (pre-ultrasound) with no ultrasound exposure. Questionnaire data were also obtained from year 1 medical students and physical diagnosis faculty to assess attitudes toward ultrasound implementation.

RESULTS

The final overall OSCE scores were graded with a 5-point Likert-type scale from unsatisfactory to outstanding. There was a significant increase in outstanding scores in the post-ultrasound compared to the pre-ultrasound group (27.0% versus 10.9%; P< .001). The post-ultrasound group had significantly (P< .05) increased first-time pass rates on blood pressure measurements, the abdominal examination, and professionalism. Student and physical diagnosis faculty questionnaire data showed an overall positive response, with most agreeing or strongly agreeing that ultrasound should be included in the future year 1 medical student curriculum.

CONCLUSIONS

Ultrasound implementation into a physical diagnosis curriculum for year 1 medical students is feasible and may improve their overall traditional physical examination skills.

Hearing, Listening, Action: Enhancing nursing practice through aural awareness education

Abstract Noise overload within the clinical environment has been found to interfere with the healing process for patients, as well as nurses ability to effectively assess patients. Awareness and responsibility for noise production begins during initial nursing training and consequently a program to enhance aural awareness skills was designed for graduate entry nursing students in an Australian university. The program utilised an innovative combination of music education activities to develop the students' ability to distinguishing individual sounds (hearing), appreciate patient's experience of sounds (listening) and improve their auscultation skills and reduce the negative effects of noise on patients (action). Using a mixed methods approach, students' reported heightened auscultation skills and greater recognition of both patients' and clinicians' aural overload. Results of this pilot suggest that music education activities can assist nursing students to develop their aural awareness and to action changes within the clinical environment to improve the patient's experience of noise.

Simulation-guided cardiac auscultation improves medical students' clinical skills: the Pavia pilot experience

Clinical evaluation is the cornerstone of any cardiac diagnosis, although excessive over-specialisation often leads students to disregard the value of clinical skills, and to overemphasize the approach to instrumental cardiac diagnosis. Time restraints, low availability of "typical" cardiac patients on whom to perform effective bedside teaching, patients' respect and the underscoring of the value of clinical skills all lead to a progressive decay in teaching. Simulation-guided cardiac auscultation may improve clinical training in medical students and residents. Harvey(©) is a mannequin encompassing more than 50 cardiac diagnoses that was designed and developed at the University of Miami (Florida, USA). One of the advantages of Harvey(©) simulation resides in the possibility of listening, comparing and discussing "real" murmurs. To objectively assess its teaching performance, the capability to identify five different cardiac diagnoses (atrial septal defect, normal young subject, mitral stenosis with tricuspid regurgitation, chronic mitral regurgitation, and pericarditis) out of more than 50 diagnostic possibilities was assessed in 523 III-year medical students (i.e. at the very beginning of their clinical experience), in 92 VI-year students, and in 42 residents before and after a formal 10-h teaching session with Harvey(©). None of them had previously experienced simulation-based cardiac auscultation in addition to formal lecturing (all three groups) and bedside teaching (VI-year students and residents). In order to assess the "persistence" of the acquired knowledge over time, the test was repeated after 3 years in 85 students, who did not repeat the formal 10-h teaching session with Harvey(©) after the III year. As expected, the overall response was poor in the "beginners" who correctly identified 11.0 % of the administered cardiac murmurs. After simulation-guided training, the ability to recognise the correct cardiac diagnoses was much better (72.0 %; p < 0.001 vs. baseline). Rather unexpectedly, before the tutorial, the performance of VI-year students and of residents was not significantly different from their III-year colleagues, since the two groups correctly identified 14.2 and 16.2 % of the diagnoses, respectively. After the tutorial, the VI-year students and the residents also improved their overall performance (to 73.1 and 76.1 %, respectively; p < 0.001 for both when compared to before the tutorial). The persistence of this capability after 3 years was remarkable, since the 85 students who repeated the test without any further exposure to the 10-h teaching session with Harvey(©) correctly identified 68.4 % of the possible cardiac diagnoses (p < 0.001 vs. baseline). These data underscore the importance of clinical training in order to improve auscultation skills in our academic setting, prompting to redesign teaching curricula. Simulation-based cardiac auscultation should be considered as the "missing link" between formal lecturing and bedside teaching of heart sounds and murmurs.

Automatic heart sound detection in pediatric patients without electrocardiogram reference via pseudo-affine Wigner-Ville distribution and Haar wavelet lifting

Having in mind the availability of electronic stethoscopes, phonocardiograms (PCGs) have become popular for cardiovascular functionality monitoring and signal processing applications. Detection of fundamental heart sounds (HSs), S1s and S2s, is considered to be a crucial step in PCG analysis. Electrocardiogram (ECG), noted as a reference signal, is often synchronously recorded in order to simplify the S1/S2 detection process. Nevertheless, electronic stethoscopes are frequently used without additional ECG equipment. We propose a new algorithm for automatic fundamental HSs detection via: joint time-frequency representation based on pseudo affine Wigner-Ville distribution (PAWVD), Haar wavelet lifting scheme (Haar-LS), normalized average Shannon energy (NASE) and autocorrelation. The performance of the proposed algorithm was calculated on both normal (50) and pathological (75) PCG recordings, eight seconds long each, contributed by 125 different pediatric patients. The algorithm showed relatively high recall (90.41%) and precision (96.39%) rates of S1/S2 detection procedure in a variety of PCG signals, without ECG as a reference. Furthermore, it indicated the ability to overcome splitting within the S1/S2 heart sounds.

Classification of prolapsed mitral valve versus healthy heart from phonocardiograms by multifractal analysis

Phonocardiography has shown a great potential for developing low-cost computer-aided diagnosis systems for cardiovascular monitoring. So far, most of the work reported regarding cardiosignal analysis using multifractals is oriented towards heartbeat dynamics. This paper represents a step towards automatic detection of one of the most common pathological syndromes, so-called mitral valve prolapse (MVP), using phonocardiograms and multifractal analysis. Subtle features characteristic for MVP in phonocardiograms may be difficult to detect. The approach for revealing such features should be locally based rather than globally based. Nevertheless, if their appearances are specific and frequent, they can affect a multifractal spectrum. This has been the case in our experiment with the click syndrome. Totally, 117 pediatric phonocardiographic recordings (PCGs), 8 seconds long each, obtained from 117 patients were used for PMV automatic detection. We propose a two-step algorithm to distinguish PCGs that belong to children with healthy hearts and children with prolapsed mitral valves (PMVs). Obtained results show high accuracy of the method. We achieved 96.91% accuracy on the dataset (97 recordings). Additionally, 90% accuracy is achieved for the evaluation dataset (20 recordings). Content of the datasets is confirmed by the echocardiographic screening.

Looking is not seeing and listening is not hearing: effect of an intervention to enhance auditory skills of graduate-entry nursing students

Inspection/observation and listening/auscultation are essential skills for health care providers. Given that observational and auditory skills take time to perfect, there is concern about accelerated students' ability to attain proficiency in a timely manner. This article describes the impact of music auditory training (MAT) for nursing students in an accelerated master's entry program on their competence in detecting heart, lung, and bowel sounds. During the first semester, a two-hour MAT session with focused attention on pitch, timbre, rhythm, and masking was held for the intervention group; a control group received traditional instruction only. Students in the music intervention group demonstrated significant improvement in hearing bowel, heart, and lung sounds (p < .0001). The ability to label normal and abnormal heart sounds doubled; interpretation of normal and abnormal lung sounds improved by 50 percent; and bowel sounds interpretation improved threefold, demonstrating the effect of an adult-oriented, creative, yet practical method for teaching auscultation.