Data Collection Using Eko Digital Devices in a Clinical Setting

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.

NCT Number	NCT07227376
Lead Sponsor	Eko Devices, Inc.
Conditions	Lung Diseases
Enrollment	250 participants
Start Date	2025-09-14
Primary Completion	2027-04-01 (estimated)
Study Completion	2027-11-30 (estimated)
Updated on ClinicalTrials.gov	2026-05-26