An observational study in Lung Diseases, sponsored by Eko Devices, Inc.. Recruiting at 2 sites in United States. Per ClinicalTrials.gov, last updated 2026-05-26.
Sponsored by Eko Devices, Inc. · Observational
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.
3,303 studies on the registry are indexed under Lung Diseases; 355 are open to participants now.
This study's planned enrollment of 250 is above the median of 157 across 929 observational studies indexed under Lung Diseases.
Browse Lung Diseases studies →Eko Devices, Inc. is the lead sponsor of 17 studies on the registry; 6 are open to participants now.
Counted across the registry records on this site, refreshed daily.
Potential research subjects with complaints of shortness of breath or relevant diagnoses like COPD/heart failure/asthma will be screened for eligibility from the upcoming clinic schedule and then recruited during their clinical appointment. Inpatients may also be identified from the EHR and recruited from inpatient units. In order to achieve the harder-to-fill buckets, it may be necessary to directly target existing registries or patient databases, and/or bring patients in for a research-specific visit. Additionally, patients seen in clinic or in hospital with no known respiratory condition will be recruited and evaluated.
Exclusion Criteria:
Use of the Eko CORE 500 digital stethoscope and 3M Littmann CORE Digital Stethoscope to listen for and record lung sounds.
Primary Objective
The primary objective of this study is to collect normal and abnormal lung sounds of up to 750 patients per study site, by having clinicians use the Eko CORE and/or Eko CORE 500 device(s) in real clinical settings, 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.
Time frame: Through study completion, an average of 8-9 months
Plan to share: No
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Eko Devices, Inc.