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Data Collection Using Eko Digital Devices in a Clinical Setting
Sponsor: Eko Devices, Inc.
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
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