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RECRUITING
NCT07227376

Data Collection Using Eko Digital Devices in a Clinical Setting

Sponsor: Eko Devices, Inc.

View on ClinicalTrials.gov

Summary

The purpose of this research is to prospectively train and validate an artificial intelligence machine learning (ML) algorithm to detect the presence of adventitious lung sounds in adults. Clinicians will use the Eko CORE and/or Eko CORE 500 device(s) in real clinical settings to collect normal and abnormal lung sounds, as part of standard of care clinical practice, which will then be used to explore an ML algorithm for classifiers for wheeze, coarse crackle, fine crackle, rhonchus, stridor, rales, and cough, as well as determine any correspondences between the type and/or location of adventitious lung sounds and the type of pulmonary conditions as reported by clinicians.

Key Details

Gender

All

Age Range

Any - Any

Study Type

OBSERVATIONAL

Enrollment

250

Start Date

2025-09-14

Completion Date

2026-07-01

Last Updated

2025-12-05

Healthy Volunteers

Not specified

Conditions

Interventions

DEVICE

Eko digital stethoscopes

Use of the Eko CORE 500 digital stethoscope and 3M Littmann CORE Digital Stethoscope to listen for and record lung sounds.

Locations (2)

Nemours Children's Health

Jacksonville, Florida, United States

Jefferson Einstein Philadelphia Hospital

Philadelphia, Pennsylvania, United States