Creating and Assessing a Voice Dataset for Automated Classification of Chronic Obstructive Pulmonary Disease

Study Overview
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Brief Summary
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This work aims to evaluate whether voice recordings collected from patients diagnosed with COPD and healthy control groups can be used to detect the disease using machine learning techniques.

Detailed Description
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Voice data and sociodemographic data on gender and age will be collected through the VoiceDiganostic application from the company Voice Diagnostic, which allows one to participate without location dependency. Participants with a diagnosis will be marked as the COPD group, and others will be marked as the healthy control group. Private information such as known comorbidities, personal security numbers, health parameters and communication information will be separately noticed in a participation table for each group. The collected data will be transformed into mathematical vocal measures called voice features. A dataset consisting of voice features in conjunction with demographics and health data will be constructed for further usage as an input to ML techniques. Descriptive statistical analysis will be held on attributes containing information on input data and gained outcomes from ML algorithms. The achieved results will be presented in the form of summary tables and graphs.

Official Title
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Creating and Assessing a Voice Dataset for Automated Classification of Chronic Obstructive Pulmonary Disease

Conditions
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Chronic Obstructive Pulmonary Disease

Intervention / Treatment
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* Other: COPD


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: being 18 years old and older. Exclusion Criteria: being under 18 years old.

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| COPD<br>Participants with clinically diagnosed Chronic obstructive pulmonary disease. Total 34 recruitment, 18 Female, 16 Male | Other: COPD<br>* A data set consisting of information from COPD and HC groups will be used to experiment with the classification performance of several Machine Learning techniques.<br>* Other names: HC;|
| HC<br>Participants without Chronic obstructive pulmonary disease diagnosis. Total 38 recruitment, 20 Female, 18 Male | Other: COPD<br>* A data set consisting of information from COPD and HC groups will be used to experiment with the classification performance of several Machine Learning techniques.<br>* Other names: HC;|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Accuracy | Binary detection performance of the ML algorithm | Week 51 | 
| Input data importance scale | Features used as input data will be ranked from most important to less important one. | Week 51 | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Automatic, Classification, COPD, Machine Learning, Mobile phone