使用智能手机进行心脏听诊：初步研究。
Cardiac Auscultation Using Smartphones: Pilot Study.
作者信息
Kang Si-Hyuck, Joe Byunggill, Yoon Yeonyee, Cho Goo-Yeong, Shin Insik, Suh Jung-Won
机构信息
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.
出版信息
JMIR Mhealth Uhealth. 2018 Feb 28;6(2):e49. doi: 10.2196/mhealth.8946.
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).
背景
心脏听诊是一种经济高效的非侵入性筛查工具，可提供有关心血管血流动力学和疾病的信息。然而，随着影像学和实验室检查的进展，心脏听诊在临床实践中的重要性未得到充分重视。智能手机的广泛使用为非医学专业用户在就诊前进行自我检查提供了机会。
目的
我们研究的目的是评估在院前阶段使用无附加设备的智能手机进行心脏听诊的可行性。
方法
我们对有正常和病理性心音的患者进行了一项试点研究。使用3部智能手机（三星Galaxy S5和Galaxy S6以及LG G3）在胸壁皮肤上记录心音。使用卷积神经网络的诊断算法对记录的心音进行处理和分类。我们评估了诊断准确性以及敏感性、特异性和预测值。
结果
共有46名参与者进行了心音记录。经过音频文件处理后，46例心音中有30例（65%）被证明可解释。心房颤动和舒张期杂音与未能获取可解释的心音显著相关。诊断算法将心音准确分类到正确类别：Galaxy S5为90%（95%CI 73%-98%）；Galaxy S6为87%（95%CI 69%-96%）；LG G3为90%（95%CI 73%-98%）。这3部设备的敏感性、特异性、阳性预测值和阴性预测值也均可接受。
结论
使用智能手机进行心脏听诊是可行的。使用卷积神经网络进行鉴别诊断具有较高的准确性。然而，仅使用内置麦克风，获取可重复且可解释的心音仍然是一项重大挑战。
试验注册
ClinicalTrials.gov NCT03273803；https://clinicaltrials.gov/ct2/show/NCT03273803（由WebCite存档于http://www.webcitation.org/6x6g1fHIu）
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