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NCT Number: NCT06512064

Acoustic Waveform Respiratory Evaluation

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.

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Key information

Conditions

Asthma Abnormalities, Multiple Airway Malacia Bronchial Diseases Bronchiectasis COPD Chronic Disease Ciliary Motility Disorders Ciliopathies Congenital Abnormalities Congenital, Hereditary, and Neonatal Diseases and Abnormalities Cystic Fibrosis Digestive System Diseases Disease Attributes Genetic Diseases, Inborn Healthy Control Hypersensitivity Hypersensitivity, Immediate Immune System Diseases Infant, Newborn, Diseases Lung Diseases Lung Diseases, Obstructive Otorhinolaryngologic Diseases Pancreatic Diseases Pathologic Processes Pathological Conditions, Signs and Symptoms Pulmonary Disease, Chronic Obstructive Respiratory Hypersensitivity Respiratory Tract Diseases

Age range

8 year–70 year

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Indiana University, Indianapolis, Indiana, United States

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About this study

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 (i.e., with both study smartphones and their own smartphone) to evaluate repeatability using diverse equipment and software platforms.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Age 8-70 years
  • Ability to perform spirometry and oscillometry
  • Signed informed consent (and assent for children as appropriate)
  • No respiratory or other major disease (for healthy controls), or physician-diagnosed asthma, COPD, CF, or other airway diseases

Exclusion criteria

  • Inability or unwillingness to perform AWARE, spirometry, or oscillometry
  • Acute or chronic illness that, at the judgement of investigators, may affect lung function and alter the results of AWARE or the reference PFTs (spirometry and AOS)

Treatment and study plan

AWARE

Diagnostic Test

AWARE testing to estimate lung function and aid in disease diagnosis

Primary outcomes

  1. Accurate and reliable disease diagnosis

    Time frame: Up to two weeks per subject

    Ability of AWARE to accurately classify subjects into the study disease categories with high accuracy (>80% sensitivity and >80% overall accuracy)

  2. Estimation of FEV1

    Time frame: Up to two weeks per subject

    Ability of AWARE to estimate FEV1 with high accuracy (<5% error compared to spirometry measures). FEV1 (forced expiratory volume in 1 second) is a measurement of how much air a person can exhale in the first second after inhaling.

  3. Estimation of FVC

    Time frame: Up to two weeks per subject

    Ability of AWARE to estimate FVC with high accuracy (<5% error compared to spirometry measures). FVC (forced vital capacity) is a measurement of the maximum amount of air a person can exhale after a deep breath in.

  4. Estimation of FEV1/FVC

    Time frame: Up to two weeks per subject

    Ability of AWARE to estimate FEV1/FVC with high accuracy (<5% error compared to spirometry measures). FEV1/FVC is the proportion of the forced vital capacity (FVC) that is exhaled in the first second (FEV1).

  5. Estimation of FEF2575

    Time frame: Up to two weeks per subject

    Ability of AWARE to estimate FEF2575 with high accuracy (<5% error compared to spirometry measures). FEF25-75% is defined as forced expiratory flow over the middle one-half of the FVC (the average flow from the point at which 25% of the FVC has been exhaled to the point at which 75% of the FVC has been exhaled).

  6. Estimation of R5

    Time frame: Up to two weeks per subject

    Ability of AWARE to estimate R5 with high accuracy (<10% error compared to oscillometry measures). R5 (also known as Rrs5), assessed by oscillometry, is the airway resistance to sound waves at a frequency of 5 Hz.

  7. Estimation of R20

    Time frame: Up to two weeks per subject

    Ability of AWARE to estimate R20 with high accuracy (<10% error compared to oscillometry measures). R20 (also known as Rrs20), assessed by oscillometry, is the airway resistance to sound waves at a frequency of 20 Hz.

  8. Estimation of R5-R20

    Time frame: Up to two weeks per subject

    Ability of AWARE to estimate R5-R20 with high accuracy (<10% error compared to oscillometry measures). R5-R20 (also known as Rrs5-Rrs20) is a measurement of small airway dysfunction typically assessed via oscillometry in which the difference in airway resistance to sound waves of 5 Hz and 20 Hz is calculated.

  9. Estimation of X5

    Time frame: Up to two weeks per subject

    Ability of AWARE to estimate X5 with high accuracy (<10% error compared to oscillometry measures). X5 (also known as Xrs5), assessed by oscillometry, is the airway reactance to sound waves at a frequency of 5 Hz.

  10. Estimation of AX

    Time frame: Up to two weeks per subject

    Ability of AWARE to estimate AX with high accuracy (<10% error compared to oscillometry measures). AX (area of reactance) is a lung function measurement of the lung's ability to store energy for passive expiration obtained via oscillometry. AX is measured by the area under the reactance curve from lowest frequency to the resonant frequency.

  11. Identification of airway changes associated disease exacerbations

    Time frame: Up to two weeks per subject

    Ability of AWARE to identify disease exacerbations (>80% sensitivity and >80% overall accuracy).

Secondary outcomes

  1. Reliable screening for disease diagnosis

    Time frame: Up to two weeks per subject

    Ability of AWARE to classify subjects into the study disease categories with adequate sensitivity (>70%) and accuracy (>50%) for use as a screening test

  2. Screening of FEV1

    Time frame: Up to two weeks per subject

    Ability of AWARE to estimate FEV1 with acceptable accuracy (<10% error) for use as a screening test.

  3. Screening of FVC

    Time frame: Up to two weeks per subject

    Ability of AWARE to estimate FVC with acceptable accuracy (<10% error) for use as a screening test

  4. Screening of FEV1/FVC

    Time frame: Up to two weeks per subject

    Ability of AWARE to estimate FEV1/FVC with acceptable accuracy (<10% error) for use as a screening test

  5. Screening of FEF2575

    Time frame: Up to two weeks per subject

    Ability of AWARE to estimate FEF2575 with acceptable accuracy (<10% error) for use as a screening test

  6. Screening of R5

    Time frame: Up to two weeks per subject

    Ability of AWARE to estimate R5 with acceptable accuracy (<20% error) for use as a screening test

  7. Screening of R20

    Time frame: Up to two weeks per subject

    Ability of AWARE to estimate R20 with acceptable accuracy (<20% error) for use as a screening test

  8. Screening of R5-R20

    Time frame: Up to two weeks per subject

    Ability of AWARE to estimate R5-R20 with acceptable accuracy (<20% error) for use as a screening test

  9. Screening of X5

    Time frame: Up to two weeks per subject

    Ability of AWARE to estimate X5 with acceptable accuracy (<20% error) for use as a screening test

  10. Screening of AX

    Time frame: Up to two weeks per subject

    Ability of AWARE to estimate AX with acceptable accuracy (<20% error) for use as a screening test

  11. Screening of airway changes associated disease exacerbations

    Time frame: Up to two weeks per subject

    Ability of AWARE to identify disease exacerbations with adequate accuracy for use as a screening test (>70% sensitivity and >50% overall accuracy)

Study contacts

Contact information is provided by the study sponsor or research team.

Elizabeth Rizzi, RN

CONTACT

[email protected]

317-626-6937

Lisa Bendy, RRT

CONTACT

[email protected]

317-278-7152

Sponsors and collaborators

Lead sponsor

Indiana University

Other

Collaborators

  • National Heart, Lung, and Blood Institute (NHLBI)
  • University of Pittsburgh

Registry information

Official study title

Advancing Telemedicine in Pulmonology: Acoustic-waveform Respiratory Evaluation (AWARE) Via Sensing and Machine Learning on Smartphones

Acronym: AWARE

Important dates

Study start
2024
Primary completion
2029
Study completion
2029
First posted
Jul 22, 2024
Registry last updated
Oct 24, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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