Can a Smartphone Listen to Your Heart? A Performance Study on Detecting Abnormalities in Your Heart Sounds

NCT ID: NCT06070298

Last Updated: 2025-04-24

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

ACTIVE_NOT_RECRUITING

Total Enrollment

577 participants

Study Classification

OBSERVATIONAL

Study Start Date

2023-12-01

Study Completion Date

2025-05-31

Brief Summary

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This observational study aims to assess the performance of the software called ausculto™. ausculto™ is a collection of computer algorithms that intend to analyse heart sounds recorded from the built-in microphone of a smartphone for abnormal sounds.

Participants will have their heart sounds recorded during their regular clinic appointment after consenting to participate in this study.

Researchers will manually annotate the recorded heart sounds to create a database for use in future training and testing of artificial intelligence (AI) intended for medical uses.

Detailed Description

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Conditions

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Valvular Heart Disease Heart Murmurs Cardiovascular Abnormalities

Study Design

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Observational Model Type

CASE_CONTROL

Study Time Perspective

CROSS_SECTIONAL

Study Groups

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Abnormal Echocardiography Diagnosis

Participants with abnormal echocardiography diagnosis within three years.

Computer algorithms

Intervention Type DIAGNOSTIC_TEST

Collection of lightweight computer algorithms called ausculto™ that is designed to perform real-time heart sound analysis to detect heart murmur.

Normal Echocardiography Diagnosis

Participants with normal echocardiography diagnosis within three years.

Computer algorithms

Intervention Type DIAGNOSTIC_TEST

Collection of lightweight computer algorithms called ausculto™ that is designed to perform real-time heart sound analysis to detect heart murmur.

Interventions

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Computer algorithms

Collection of lightweight computer algorithms called ausculto™ that is designed to perform real-time heart sound analysis to detect heart murmur.

Intervention Type DIAGNOSTIC_TEST

Other Intervention Names

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ausculto™ Vitogram™

Eligibility Criteria

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Inclusion Criteria

* Age: ≥22 years (adult)
* Outpatients who have undergone echocardiography within 3 years at their normal non-research follow-up clinic visit appointment

Exclusion Criterion:

* Implanted active medical devices in the torso, such as pacemakers and defibrillators
Minimum Eligible Age

22 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Laboratory of Data Discovery for Health

UNKNOWN

Sponsor Role collaborator

The University of Hong Kong

OTHER

Sponsor Role collaborator

Wong Chun Ka

OTHER

Sponsor Role lead

Responsible Party

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Wong Chun Ka

Clinical Assistant Professor

Responsibility Role SPONSOR_INVESTIGATOR

Principal Investigators

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Chun Ka Wong, MBBS

Role: PRINCIPAL_INVESTIGATOR

The University of Hong Kong

Locations

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Queen Mary Hospital

Hong Kong, Hong Kong SAR, China

Site Status

Countries

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China

Other Identifiers

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AUSC1

Identifier Type: -

Identifier Source: org_study_id

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