Data Collection Using Eko Digital Devices in a Clinical Setting

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

RECRUITING

Total Enrollment

250 participants

Study Classification

OBSERVATIONAL

Study Start Date

2025-09-14

Study Completion Date

2026-07-01

Brief Summary

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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.

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Detailed Description

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Conditions

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Lung Diseases

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Interventions

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Eko digital stethoscopes

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

Intervention Type DEVICE

Eligibility Criteria

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Inclusion Criteria

* Suspected or diagnosed lower respiratory condition OR Presence of wheeze, coarse crackle, fine crackle, rhonchus, stridor, rales, and cough discovered during routine auscultation
* Normal patients with no adventitious lung sounds
* Adults and pediatric patients (as available)