Evaluation of an Automated Smartphone-based Digital Auscultation Application for Detecting Abnormal Heart Sounds Using Deep Learning Techniques

Completed

• Conditions: Valvular Heart Disease

• Registration Number: NCT05325723
• Lead Sponsor: University Hospital, Basel, Switzerland

Brief Summary

This pilot study is to investigate the feasibility of obtaining medical grade audio phonocardiogram (PCG) recordings using a smartphone-based auscultation device in the first step. The ability to determine Valvular Heart Disease (VHD) (i.e., presence or absence of cardiac murmurs) using novel handheld CAA-devices shall be analyzed and first data on a smartphone-based auscultation in a hospital setting shall be collected. In further studies, the data provided from this study can be used to investigate the potential diagnostic use of such devices in the ambulatory and stationary care scenarios.

Detailed Description

Cardiac auscultation is considered to be highly subjective with substantial varying sensitivities and specificities in regard of the practitioners' expertise. Computer-assisted auscultation (CAA) aims to provide increased objectivity. CAA makes auscultation procedure less operator-dependent, approximate inter-examiner differences and may reduce uncertainties in the course of the examination. With the introduction of modern Machine Learning software libraries and ever-growing computational resources CAA has advanced significantly and is now able to classify heart sounds and murmurs into normal and abnormal, using complex spectro-temporal signal processing techniques and neural network pathways. CAA has simultaneously made the shift from the deployment on computers to consumer smartphones. A benefit of CAA can be expected from the smartphone alone in terms of cost, application range, the clinical validity of such algorithms should now be measured in this pilot study. This pilot study is to investigate the feasibility of obtaining medical grade audio phonocardiogram (PCG) recordings using a smartphone-based auscultation device in the first step. In further studies, the data provided from this study can be used to investigate the potential diagnostic use of such devices in the ambulatory and stationary care scenarios.

Study Timeline

• Study First Submitted: 2022-04-05
• Study First Submitted QC: 2022-04-05
• Study First Posted: 2022-04-13
• Study Start: 2022-08-30
• Primary Completion: 2023-07-31
• Study Completion: 2023-07-31
• Status Verified: 2023-09
• Last Update Submitted: 2023-09-13
• Last Update Posted: 2023-09-14

Recruitment & Eligibility

• Status: COMPLETED
• Sex: All
• Target Recruitment: 102

Inclusion Criteria

• Older or equal than 18 years of age
• Referred for an echocardiogram
• Able to provide informed consent

Exclusion Criteria

• Confirmed arrythmia
• Prior valvular intervention
• Evidence of congenital heart disease

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Determination of Valvular Heart Disease (VHD) (i.e., presence or absence of cardiac murmurs)	one time assessment at baseline (approx. 5 minutes)	Ability to determine VHD (i.e., presence or absence of cardiac murmurs) using novel handheld CAA-devices is investigated by collection of data on a smartphone-based auscultation in a hospital setting.

Trial Locations

Locations (1)

University Hospital Basel, Division of Internal Medicine; 🇨🇭 Basel, Switzerland