Voice Analysis in Asthmatic Patients With Machine Learning Models

NCT06820671 | Completed

• 1 other identifier: Med-ML001
• Study Type: observational
• Target: 344
• Locations: 1 country
• Sites: 1

Brief 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. 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.

Conditions

Asthma

Keywords

voice biomarker; machine learning

Outcome Measures

Primary Outcomes (1)

• Comparison of voice characteristics

  Comparison of voice characteristics in asthmatic patients and healthy individuals with machine learning and deep learning

  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

  A maximum of 7 voice sample recording in one session for each participant, 2 minutes total.

Study Arms (2)

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

Other: Recording voice samples

Healthy Group

Healthy participants Adults aged between 18-65 years of age with good general health

Other: Recording voice samples

Interventions

Recording voice samples OTHER

Voice recording with * reading the standard text * repeating the test words * vowel elicitation of 'a' and 'o' vowels for 5-10 seconds

Asthmatic Group; Healthy Group

Eligibility Criteria

• Age: 18 Years - 65 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

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'.

You may qualify if:

• Patients diagnosed with asthma according to GINA criteria and Pulmonary Function Test, and followed for at least three months
• years of age.
• Sign an informed consent document
• Able to comply with the study protocol during the study period.

You may not qualify if:

• None
• Healthy Group
• Healthy participants between 18-65 years of age
• Good general health
• 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.
• None

Sponsors & Collaborators

• MED-CASE: lead
• Saglik Bilimleri Universitesi: collaborator
• Yedikule Training and Research Hospital: collaborator

Study Sites (1)

University of Health Sciences Yedikule Chest Diseases and Thoracic Surgery Training And Reseaerch Hospital

Istanbul, 34100, Turkey (Türkiye)

Location

MeSH Terms

Conditions

Asthma

Condition Hierarchy (Ancestors)

Bronchial Diseases; Respiratory Tract Diseases; Lung Diseases, Obstructive; Lung Diseases; Respiratory Hypersensitivity; Hypersensitivity, Immediate; Hypersensitivity; Immune System Diseases

Study Design

• Study Type: observational
• Observational Model: CASE CONTROL
• Time Perspective: CROSS SECTIONAL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: January 15, 2025
• First Posted: February 11, 2025
• Study Start: January 9, 2024
• Primary Completion: August 5, 2024
• Study Completion: February 20, 2025
• Last Updated: May 18, 2025

Record last verified: 2025-05

Data Sharing

• IPD Sharing: Will not share

Locations

TU (1)