Data Collection Using Eko Digital Devices in a Clinical Setting

NCT07227376 | Recruiting

• 1 other identifier: 2022.5 V10.0
• Study Type: observational
• Target: 250
• Locations: 1 country
• Sites: 2

Brief 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.

Conditions

Lung Diseases

Keywords

lung sounds; adventitious lung sounds; abnormal lung sounds

Outcome Measures

Primary Outcomes (1)

• 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.

  Through study completion, an average of 8-9 months

Interventions

Eko digital stethoscopes DEVICE

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

Eligibility Criteria

• Sex: all
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

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.

You may qualify if:

• 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)

You may not qualify if:

• Unable to have multiple recordings taken on chest and back (e.g. compromised mobility)
• On mechanical ventilation

Sponsors & Collaborators

• Eko Devices, Inc.: lead

Study Sites (2)

Nemours Children's Health

Jacksonville, Florida, 32256, United States

RECRUITING

Jefferson Einstein Philadelphia Hospital

Philadelphia, Pennsylvania, 19141, United States

RECRUITING

MeSH Terms

Conditions

Lung Diseases; Respiratory Sounds

Condition Hierarchy (Ancestors)

Respiratory Tract Diseases; Signs and Symptoms, Respiratory; Signs and Symptoms; Pathological Conditions, Signs and Symptoms

Central Study Contacts

Clinical Research Associate

CONTACT

8443563384; jackrin.walsh@ekohealth.com

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: October 24, 2025
• First Posted: November 12, 2025
• Study Start: September 14, 2025
• Primary Completion: April 1, 2026
• Study Completion (Estimated): July 1, 2026
• Last Updated: December 5, 2025

Record last verified: 2025-10

Data Sharing

• IPD Sharing: Will not share

Locations

US (2)