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

NCT ID: NCT05325723

Last Updated: 2023-09-14

Basic Information

• Recruitment Status: COMPLETED
• Total Enrollment: 102 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2022-08-30
• Study Completion Date: 2023-07-31

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.

Conditions

Valvular Heart Disease

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: PROSPECTIVE

Study Groups

Intervention group

1. 30 second audio phonocardiogram (PCG) recordings at each of the five standard cardiac auscultatory positions using an Apple iPhone®.

2. the assessment of VHD by echocardiogram, as reported by the echocardiography laboratory.

No interventions assigned to this group

Eligibility Criteria

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

• Minimum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

University Hospital, Basel, Switzerland

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Jens Eckstein, Prof. Dr. med.

Role: PRINCIPAL_INVESTIGATOR

University Hospital Basel, Division of Internal Medicine

Locations

University Hospital Basel, Division of Internal Medicine

Basel, , Switzerland

Countries

Switzerland

Other Identifiers

2021-02515; am21Eckstein

Identifier Type: -

Identifier Source: org_study_id