Data Collection Using Eko Devices in a Clinical Setting
ConditionLung Diseases
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorEko Devices, Inc.
About this trial
The main objectives of the study are to: train and validate binary classifiers for wheeze, coarse crackle, fine crackle, rhonchus, stridor, rales, and cough, as well as determine correspondence between type/location of adventitious lung sound and type of pulmonary condition.
Eligibility criteria
This trial accepts healthy volunteersQualifiers
Patients 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, over 18 years old
Able to provide verbal consent
Disqualifiers
Patients unable to have multiple recordings taken on chest and back (e.g. compromised mobility)
Patients on mechanical ventilation
Patients unwilling or unable to provide informed consent
Trial 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.
Trial design
Design model
Cohort
Time perspective
Prospective
Treatments tested in this trial
Eko digital stethoscopes
DeviceUse of the Eko CORE 500 digital stethoscope and 3M Littmann CORE Digital Stethoscope to listen for and record lung sounds.
Treatment groups
No treatment groups listed
Trial outcomes
Primary outcomes
1
Primary Objective: Collection of Lung Sound Recordings to Explore Machine Learning Algorithm for Classifying Adventitious Lung Sounds
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.
Time frame
14-15 monthsSponsors and contacts
Click on the lead sponsor to view all of their trials.
Source ClinicalTrials.gov