Ignite Creation Date:
2024-10-26 @ 3:35 PM
Last Modification Date:
2024-10-26 @ 3:35 PM
Study NCT ID:
NCT06512064
Status:
RECRUITING
Last Update Posted:
None
First Post:
2024-06-26
Brief Title:
Acoustic Waveform Respiratory Evaluation
Sponsor:
None
Organization:
None
Study Overview
Official Title:
Advancing Telemedicine in Pulmonology Acoustic-waveform Respiratory Evaluation AWARE Via Sensing and Machine Learning on Smartphones
Status:
RECRUITING
Status Verified Date:
2024-09
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
No
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
AWARE
Brief Summary:
The study will evaluate the feasibility of using smartphone speakers and microphones to evaluate the caliber of the airways detect airway obstruction aid in airway disease diagnosis and identify disease exacerbations
Detailed Description:
Asthma and COPD respectively affect millions of people in the US Chronic lower respiratory diseases represented the fourth leading cause of death in the country before the pandemic For these and other pulmonary diseases like cystic fibrosis CF monitoring disease remotely but objectively could lead to marked improvements in disease control quality of life and overall prognosis However current disease monitoring and management often rely on subjective symptom report and objective pulmonary function tests PFTs are often only done a handful of times a year at subspecialty referral centers The primary hypothesis for this study is that smartphone-based sensing and machine learning ML approaches can advance pulmonary telemedicine by enabling comprehensive pulmonary disease evaluation with high accuracy reliability and adaptability The investigators further hypothesize that AWARE can accurately help identify different lung diseases estimate lung function and detect changes associated with exacerbations In Aim 1 investigators will develop and improve a smartphone sensing approach as an accurate and reliable aide in airway disease diagnosis Investigators will recruit a sample of healthy individuals and individuals with asthma COPD CF and other airway diseases to assess whether AWARE can accurately classify subjects in their disease groups In Aim 2 investigators will improve the ML approach to estimate lung function accurately and adaptively including traditional PFT indices from spirometry and impulse oscillometry And in Aim 3 investigators will develop deep learning techniques to identify changes in airway conditions associated disease exacerbations by performing AWARE during stable disease and acute exacerbations For these aims investigators will recruit a cohort of pediatric and adult subjects with a wide range of demographic and anthropometric characteristics to have adequate representation of various airway diseases a broad range of lung function and the ability to obtain measurements during acute disease exacerbations The study protocol will include study questionnaires anthropometry body composition and three sets of PFTs spirometry oscillometry and AWARE A subgroup of subjects will additionally perform AWARE at home for up to two weeks allowing investigators to evaluate supervised vs unsupervised and in-clinic vs at-home measurements Similarly a subgroup of subjects will perform AWARE dual testing ie with both study smartphones and their own smartphone to evaluate repeatability using diverse equipment and software platforms
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
None
Is a FDA Regulated Device?:
None
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None