Lung DiseasesNCT07360522
Data Collection For Adventitious Lung Sounds Algorithm Using Eko Digital Devices in a Clinical Setting
An observational study of Lung Diseases, run by Eko Devices, Inc. at 1 site in United States.
Trial summary
The purpose of this research is to collect patient lung sounds in order to develop an artificial machine learning algorithm that can potentially tell a doctor if a patient is at risk of certain lung conditions. Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Lung Diseases
- What is being tested?
- Eko digital stethoscopes
- Type of treatment
- Medical device
- How many people
- 750 participants
- Where
- 1 siteUnited States
- Study dates
- 23 Aug 2024to 30 Nov 2027
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
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.
Who may be able to join
- 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 patients (18 years or older)
Who cannot join
- Unable to have multiple recordings taken on chest and back (e.g. compromised mobility)
- On mechanical ventilation
Trial locations and contacts
1 site in 1 country.
About this study
The purpose of this research is to collect patient lung sounds in order to develop an artificial machine learning algorithm that can potentially tell a doctor if a patient is at risk of certain lung conditions.
Read the detailed description
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
- Being tested
- Eko digital stethoscopes
- Keywords
- lung sounds, adventitious lung sounds, abnormal lung sounds
- Medical subject headings
- Lung Diseases, Respiratory Sounds
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Eko digital stethoscopesDevice
Use of the Eko CORE 500 digital stethoscope and 3M Littmann CORE Digital Stethoscope to listen for and record lung sounds.
What is being measured
The primary outcome is the main question the study is designed to answer.
Lung Sounds Collected from Number of Patients
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.
Measured: Through study completion, an average of 8 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted22 Jan 2026
- Study start23 Aug 2024
- Primary completion21 Jul 2025
- Study completion30 Nov 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Lung DiseasesStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 750 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Eko Devices, Inc.
- Sponsor type
- Industry (pharma, biotech, devices)
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07360522
- Sponsor's protocol ID
- 2024.2
- Status last verified
- May 2026
- First submitted
- 24 Feb 2025
- Last updated
- 26 May 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 26 May 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Data Collection For Adventitious Lung Sounds Algorithm Using Eko Digital Devices in a Clinical Setting
- ClinicalTrials.gov ID
- NCT07360522
- Acronym / sponsor ID
- 2024.2
- Conditions
- Lung Diseases
- Keywords
- lung sounds, adventitious lung sounds, abnormal lung sounds
- Study type
- Observational
- Recruitment status
- Active, not recruiting
- Enrolment
- 750 participants (estimated)
- Lead sponsor
- Eko Devices, Inc.Industry (pharma, biotech, devices)
- Study start
- 23 Aug 2024 (actual)
- Primary completion
- 21 Jul 2025 (actual)
- Study completion
- 30 Nov 2027 (estimated)
- First posted
- 22 Jan 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The purpose of this research is to collect patient lung sounds in order to develop an artificial machine learning algorithm that can potentially tell a doctor if a patient is at risk of certain lung conditions.
Detailed description
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.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- 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.
Key inclusion criteria (3 listed)
- 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 patients (18 years or older)
Key exclusion criteria (2 listed)
- Unable to have multiple recordings taken on chest and back (e.g. compromised mobility)
- On mechanical ventilation
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Eko digital stethoscopesUse of the Eko CORE 500 digital stethoscope and 3M Littmann CORE Digital Stethoscope to listen for and record lung sounds. | Device | – |
Primary outcome
Lung Sounds Collected from Number of Patients
Time frame: Through study completion, an average of 8 months
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.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 26 May 2026.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Lung Diseases, run by Eko Devices, Inc. at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: under way, not looking for participants, as of the sponsor's last update on 26 May 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Lung Sounds Collected from Number of Patients (time frame: Through study completion, an average of 8 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 26 May 2026.