AsthmaNCT06820671
Voice Analysis in Asthmatic Patients With Machine Learning Models
An observational study of Asthma, run by MED-CASE at 1 site in Turkey (Türkiye).
Trial summary
Asthma can lead to various factors that impair voice production, including airway restriction, inflammation, and mucus production, resulting in changes in voice frequency and amplitude. Therefore, voice analysis may serve as an indicator of respiratory diseases. Read more about this study
- Who is it for?
- Ages 18 to 65 yearsHealthy volunteers can take part
- Conditions the study is for
- Asthma
- What is being tested?
- Recording voice samples
- How many people
- 344 participants
- Where
- 1 siteTurkey (Türkiye)
- Study dates
- 9 Jan 2024to 20 Feb 2025
- Phase
- Observational
- Are there results?
- None posted in the registry
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 to 65 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: Patients who admitted at Yedikule Chest Diseases and Thoracic Surgery Training And Research Hospital who meet eligibility criteria will be enrolled for 'Asthmatic Group'. Healthy relatives of the patients and other healthy individuals at the hospital will be enrolled for 'Healthy Group'.
Who may be able to join
- Patients diagnosed with asthma according to GINA criteria and Pulmonary Function Test, and followed for at least three months
- 18-65 years of age.
- Sign an informed consent document
- Able to comply with the study protocol during the study period.
- Healthy participants between 18-65 years of age
- Good general health
Show all 9Show fewer
- No history of chronic respiratory disorders
- No history of chronic systemic disorders
- No history of upper respiratory tract infections within five days prior voice recording.
Who cannot join
- None
- Healthy Group
- None
Trial locations and contacts
1 site in 1 country.
Turkey (Türkiye)1 site
University of Health Sciences Yedikule Chest Diseases and Thoracic Surgery Training And Reseaerch Hospital
Istanbul, 34100
About this study
Official title: Voice Analysis in Asthmatic Patients and Healthy Individuals: Comparative Evaluation of Asthma Control Levels and Voice Characteristics With Machine Learning Models
Asthma can lead to various factors that impair voice production, including airway restriction, inflammation, and mucus production, resulting in changes in voice frequency and amplitude. Therefore, voice analysis may serve as an indicator of respiratory diseases.
A national, observational, case-control study is planned in Türkiye to analyze differences in voice between healthy subjects and asthmatic patients and to assess voice analysis techniques for determining an effective biomarker for asthma control using a machine learning model.
Read the detailed description
Asthma is a disease characterized by chronic inflammation. Based on the frequency of symptoms and the use of reliever medications, the disease can be classified as either 'controlled' or 'uncontrolled'. Currently, GINA criteria and Asthma Control Test can be used to evaluate asthma control.
The relationship between respiratory functions and speech has been previously studied, revealing that voice changes can occur in asthmatic patients due to symptom presence. Asthma can lead to various factors that impair voice production, including airway restriction, inflammation, and mucus production, resulting in changes in voice frequency and amplitude. Therefore, voice analysis may serve as an indicator of respiratory diseases. Understanding the alterations in phonation/voice due to the underlying disease is crucial.
This study seeks to analyze differences in voice between healthy subjects and asthmatic patients and to assess voice analysis techniques for determining an effective biomarker for asthma control using a machine learning model.
This is a national, observational, cross-sectional study that will be conducted in Türkiye. The study consists of two stages: in the first stage, a machine learning (ML) model will be developed using voice data collected from both healthy individuals and patients diagnosed with asthma. In the second stage, this ML model will be tested to detect voice differences among patients at different levels of asthma control.
- Conditions
- Asthma
- Being tested
- Recording voice samples
- Keywords
- voice biomarker, machine learning
- Medical subject headings
- Asthma
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Recording voice samplesOther
Voice recording with
- reading the standard text
- repeating the test words
- vowel elicitation of 'a' and 'o' vowels for 5-10 seconds
| Study group | Role | What they receive |
|---|---|---|
| Asthmatic Group | Diagnosed asthma patients Adults aged between 18 and 65 years of age who have been diagnosed with asthma and followed-up for at least 3 months Receives: Other: Recording voice samples | |
| Healthy Group | Healthy participants Adults aged between 18-65 years of age with good general health Receives: Other: Recording voice samples |
What is being measured
The primary outcome is the main question the study is designed to answer.
Comparison of voice characteristics
Comparison of voice characteristics in asthmatic patients and healthy individuals with machine learning and deep learning
Measured: One session, a maximum of 7 voice sample recording in one session for each participant, 2 minutes total.
Secondary outcomes (1)
Classification of voice characteristics
Classification of voice characteristics according to Global Initiative for Asthma - (GINA) criteria using machine learning and deep learning
Measured: A maximum of 7 voice sample recording in one session for each participant, 2 minutes total.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted11 Feb 2025
- Study start9 Jan 2024
- Primary completion5 Aug 2024
- Study completion20 Feb 2025
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for AsthmaStudies 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
- Case-control
- Time perspective
- Cross-sectional
- Enrolment
- 344 participants (actual)
Sponsor and investigators
- Lead sponsor
- MED-CASE
- Sponsor type
- University, hospital or other
- Collaborators
- Saglik Bilimleri Universitesi, Yedikule Training and Research Hospital
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06820671
- Sponsor's protocol ID
- Med-ML001
- Status last verified
- May 2025
- First submitted
- 15 Jan 2025
- Last updated
- 18 May 2025
- 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 18 May 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Voice Analysis in Asthmatic Patients and Healthy Individuals: Comparative Evaluation of Asthma Control Levels and Voice Characteristics With Machine Learning Models
- ClinicalTrials.gov ID
- NCT06820671
- Acronym / sponsor ID
- Med-ML001
- Conditions
- Asthma
- Keywords
- voice biomarker, machine learning
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 344 participants (actual)
- Lead sponsor
- MED-CASEUniversity, hospital or other
- Collaborators
- Saglik Bilimleri Universitesi, Yedikule Training and Research Hospital
- Study start
- 9 Jan 2024 (actual)
- Primary completion
- 5 Aug 2024 (actual)
- Study completion
- 20 Feb 2025 (actual)
- First posted
- 11 Feb 2025 (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.
Asthma can lead to various factors that impair voice production, including airway restriction, inflammation, and mucus production, resulting in changes in voice frequency and amplitude. Therefore, voice analysis may serve as an indicator of respiratory diseases.
A national, observational, case-control study is planned in Türkiye to analyze differences in voice between healthy subjects and asthmatic patients and to assess voice analysis techniques for determining an effective biomarker for asthma control using a machine learning model.
Detailed description
Asthma is a disease characterized by chronic inflammation. Based on the frequency of symptoms and the use of reliever medications, the disease can be classified as either 'controlled' or 'uncontrolled'. Currently, GINA criteria and Asthma Control Test can be used to evaluate asthma control.
The relationship between respiratory functions and speech has been previously studied, revealing that voice changes can occur in asthmatic patients due to symptom presence. Asthma can lead to various factors that impair voice production, including airway restriction, inflammation, and mucus production, resulting in changes in voice frequency and amplitude. Therefore, voice analysis may serve as an indicator of respiratory diseases. Understanding the alterations in phonation/voice due to the underlying disease is crucial.
This study seeks to analyze differences in voice between healthy subjects and asthmatic patients and to assess voice analysis techniques for determining an effective biomarker for asthma control using a machine learning model.
This is a national, observational, cross-sectional study that will be conducted in Türkiye. The study consists of two stages: in the first stage, a machine learning (ML) model will be developed using voice data collected from both healthy individuals and patients diagnosed with asthma. In the second stage, this ML model will be tested to detect voice differences among patients at different levels of asthma control.
Study design
- Observational model
- Case-control
- Time perspective
- Cross-sectional
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Asthmatic Group | – | Other: Recording voice samplesDiagnosed asthma patients Adults aged between 18 and 65 years of age who have been diagnosed with asthma and followed-up for at least 3 months |
| Healthy Group | – | Other: Recording voice samplesHealthy participants Adults aged between 18-65 years of age with good general health |
Who may qualify
- Ages
- 18 to 65 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- Patients who admitted at Yedikule Chest Diseases and Thoracic Surgery Training And Research Hospital who meet eligibility criteria will be enrolled for 'Asthmatic Group'. Healthy relatives of the patients and other healthy individuals at the hospital will be enrolled for 'Healthy Group'.
Key inclusion criteria (9 listed)
- Patients diagnosed with asthma according to GINA criteria and Pulmonary Function Test, and followed for at least three months
- 18-65 years of age.
- Sign an informed consent document
- Able to comply with the study protocol during the study period.
- Healthy participants between 18-65 years of age
Key exclusion criteria (3 listed)
- None
- Healthy Group
- None
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 |
|---|---|---|
| Recording voice samplesVoice recording with * reading the standard text * repeating the test words * vowel elicitation of 'a' and 'o' vowels for 5-10 seconds | Other | Asthmatic Group, Healthy Group |
Primary outcome
Comparison of voice characteristics
Time frame: One session, a maximum of 7 voice sample recording in one session for each participant, 2 minutes total.
Comparison of voice characteristics in asthmatic patients and healthy individuals with machine learning and deep learning
1 secondary outcome
Classification of voice characteristics
Time frame: A maximum of 7 voice sample recording in one session for each participant, 2 minutes total.
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 18 May 2025.
- 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 Asthma, run by MED-CASE at 1 site in Turkey (Türkiye).
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 9 inclusion and 3 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: finished, as of the sponsor's last update on 18 May 2025. 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 Turkey (Türkiye). 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?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
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?
Comparison of voice characteristics (time frame: One session, a maximum of 7 voice sample recording in one session for each participant, 2 minutes total.). 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 18 May 2025.