A portable graphical representation tool for phonocardiograms

Reed, Nancy E.; Nie, Yanhan; Mahnke, C. Becket

doi:10.1109/iembs.2009.5332544

Cited by 5 publications

(5 citation statements)

References 12 publications

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“…Visualizing lung sounds in lung auscultation can boost medical students' confidence in lung auscultation. In the auscultation of heart sounds, the visualization of the timing of rhythm and murmur has been used [25]. Lung sounds have often been visualized in textbooks and reports [1,18].…”

Section: Plos Onementioning

confidence: 99%

The effects of simple graphical and mental visualization of lung sounds in teaching lung auscultation during clinical clerkship: A preliminary study

et al. 2023

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Introduction The study aimed to evaluate visualization-based training’s effects on lung auscultation during clinical clerkship (CC) in the Department of Respiratory Medicine on student skills and confidence. Methods The study period was December 2020–November 2021. Overall, 65 students attended a lecture on lung auscultation featuring a simulator (Mr. Lung™). Among them, 35 (visualization group) received additional training wherein they were asked to mentally visualize lung sounds using a graphical visualized lung sounds diagram as an example. All students answered questions on their self-efficacy regarding lung auscultation before and after four weeks of CC. They also took a lung auscultation test with the simulator at the beginning of CC (pre-test) and on the last day of the third week (post-test) (maximum score: 25). We compared the answers in the questionnaire and the test scores between the visualization group and students who only attended the lecture (control group, n = 30). The Wilcoxon signed-rank test and analysis of covariance were used to compare the answers to the questionnaire about confidence in lung auscultation and the scores of the lung auscultation tests before and after the training. Results Confidence in auscultation of lung sounds significantly increased in both groups (five-point Likert scale, visualization group: pre-questionnaire median 1 [Interquartile range 1] to post-questionnaire 3 [1], p<0.001; control group: 2 [1] to 3 [1], p<0.001) and was significantly higher in the visualization than in the control group. Test scores increased in both groups (visualization group: pre-test 11 [2] to post-test 15 [4], p<0.001; control group: 11 [5] to 14 [4], p<0.001). However, there were no differences between both groups’ pre and post-tests scores (p = 0.623). Conclusion Visualizing lung sounds may increase medical students’ confidence in their lung auscultation skills; this may reduce their resistance to lung auscultation and encourage the repeated auscultation necessary to further improve their long-term auscultation abilities.

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Section: Plos Onementioning

confidence: 99%

The effects of simple graphical and mental visualization of lung sounds in teaching lung auscultation during clinical clerkship: A preliminary study

et al. 2023

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“…There was a large variety in the descriptions of the waveforms. A graphical representation was usually used that displayed parts both above and below the center axis, as they appeared in the raw signal [28]. A simpler graphical representation of heart sounds was also shown as only half of the signal above the X-axis [1].…”

Section: Discussionmentioning

confidence: 99%

Development of a Smartphone App for Visualizing Heart Sounds and Murmurs

Mamorita¹,

Arisaka²,

Isonaka³

et al. 2017

Cardiology

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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.

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“…[12], [13] proposed a model based approach which finds prominence in conceptualization of system depicted in the dissertation. [12], [13] designed a model for HS generation and characterizing them based on the model for determining clinically important feature. They also presented a prototype system for HS analysis using wavelets and neural networks based classifiers.…”

Section: Clinical Significance and State Of The Artmentioning

confidence: 99%

Practice of Cardiac Auscultation: Clinical perspectives and its implications on computer aided diagnosis

Mandal¹,

et al. 2014

Preprint

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Study of the disease demographics in human population indicates that cardiac ailments are the primary cause of premature death, and a need for emergent technologies is felt to address the rising trend. However, development of automated heart sound analysis system and its usage at the grassroot levels for cardiac pre-screening have been hindered by the lack proper understanding of the intrinsic characteristics of cardiac auscultation. In this article we present an investigatory report based on a nationwide survey conducted on the practice of cardiac auscultation for determination of its effectiveness in diagnosis. The aims are to achieve better validation of heart sound acquisition methods and use the clinical feedback from cardiologists for improvements in the classification of the cardiac abnormalities. Results obtained from six different classifiers used in the study are illustrated, which show a remarkable specificity using an improvised classification hierarchy, derived based on clinical recommendations. The study addresses the needs for better understanding of the relevancy of heart sound signal parameters, recording transducers, recording location and the inherent complexity associated in interpretation of heart sounds, specially in noisy environments of out-patient departments and primary healthcare centers. Further, the inter-relationship between heart sound and other advance medical imaging modalities, and the need for more focused training in cardiac auscultation among the medical and paramedical staff is investigated.

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A portable graphical representation tool for phonocardiograms

Cited by 5 publications

References 12 publications

The effects of simple graphical and mental visualization of lung sounds in teaching lung auscultation during clinical clerkship: A preliminary study

The effects of simple graphical and mental visualization of lung sounds in teaching lung auscultation during clinical clerkship: A preliminary study

Development of a Smartphone App for Visualizing Heart Sounds and Murmurs

Practice of Cardiac Auscultation: Clinical perspectives and its implications on computer aided diagnosis

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