JMIR Mhealth Uhealth. 2018;6(2):e49.

Cardiac Auscultation Using Smartphones: Pilot Study.

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제1저자 강시혁 · 교신저자 서정원

PMID 29490899 PMC5853766 DOI 10.2196/mhealth.8946 IF 6.3 순환기내과

소속 (3)

Division of Cardiology, Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam-si, Republic Of Korea.
School of Computing, Korea Advanced Institute of Science and Technology, Daejeon, Republic Of Korea.
Division of Cardiology, Cardiovascular Center, Seoul National University Bundang Hospital, Seongnam-si, Republic Of Korea.

Abstract

BACKGROUND Cardiac auscultation is a cost-effective, noninvasive screening tool that can provide information about cardiovascular hemodynamics and disease. However, with advances in imaging and laboratory tests, the importance of cardiac auscultation is less appreciated in clinical practice. The widespread use of smartphones provides opportunities for nonmedical expert users to perform self-examination before hospital visits.

OBJECTIVE The objective of our study was to assess the feasibility of cardiac auscultation using smartphones with no add-on devices for use at the prehospital stage.

METHODS We performed a pilot study of patients with normal and pathologic heart sounds. Heart sounds were recorded on the skin of the chest wall using 3 smartphones: the Samsung Galaxy S5 and Galaxy S6, and the LG G3. Recorded heart sounds were processed and classified by a diagnostic algorithm using convolutional neural networks. We assessed diagnostic accuracy, as well as sensitivity, specificity, and predictive values.

RESULTS A total of 46 participants underwent heart sound recording. After audio file processing, 30 of 46 (65%) heart sounds were proven interpretable. Atrial fibrillation and diastolic murmur were significantly associated with failure to acquire interpretable heart sounds. The diagnostic algorithm classified the heart sounds into the correct category with high accuracy: Galaxy S5, 90% (95% CI 73%-98%); Galaxy S6, 87% (95% CI 69%-96%); and LG G3, 90% (95% CI 73%-98%). Sensitivity, specificity, positive predictive value, and negative predictive value were also acceptable for the 3 devices.

CONCLUSIONS Cardiac auscultation using smartphones was feasible. Discrimination using convolutional neural networks yielded high diagnostic accuracy. However, using the built-in microphones alone, the acquisition of reproducible and interpretable heart sounds was still a major challenge.

TRIAL REGISTRATION ClinicalTrials.gov NCT03273803; https://clinicaltrials.gov/ct2/show/NCT03273803 (Archived by WebCite at http://www.webcitation.org/6x6g1fHIu).

©Si-Hyuck Kang, Byunggill Joe, Yeonyee Yoon, Goo-Yeong Cho, Insik Shin, Jung-Won Suh. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 28.02.2018.

Keywords

cardiac auscultationmobile health carephysical examinationsmartphonetelemedicine

Figures

**Figure 1** Heart sound recording using a smartphone app. Left: illustration of how the heart sounds were recorded in this study. Smartphones were placed directly on the chest wall; a dedicated app was used with no add-on devices. Middle and right: representative screenshots of the app (called CPstethoscope) developed for this study. ECG: electrocardiogram.

**Figure 2** Diagnostic performance of each study device. Bold broken lines indicate diagnostic accuracy. FN: false negative; FP: false positive; TN: true negative; TP: true positive.

**Figure 3** Representative phonocardiograms and spectrograms. (A) Normal heart sounds from the aortic area of a 22-year-old man with a history of vasovagal syncope. (B) Midsystolic ejection murmur from the aortic area of an 83-year-old woman with aortic stenosis, which was classified as a systolic murmur. (C) Systolic murmur from the mitral area of a 63-year-old woman with mitral valve prolapse and mitral regurgitation, which was classified as a systolic murmur.

그림 출처: PubMed Central 공개 논문 (PMC5853766)

Conflict of interest statement

Conflicts of Interest: None declared.

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