Vowel Segmentation for Classification of Chronic Obstructive Pulmonary Disease Using Machine Learning

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

ACTIVE_NOT_RECRUITING

Total Enrollment

68 participants

Study Classification

OBSERVATIONAL

Study Start Date

2023-11-28

Study Completion Date

2024-11-30

Brief Summary

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This work aims to evaluate whether the segmentation of vowel recordings collected from patients diagnosed with COPD and healthy control groups can increase the classification precision of machine learning techniques.

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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. Collected vowel recordings will be segmented and tested to determine whether some segments contain more information for the discrimination of COPD from healthy control groups.

Each segment 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 each segment which in turn will be evaluated for classification performance using several machine learning algorithms.

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.

Conditions

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Chronic Obstructive Pulmonary Disease

Study Design

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Observational Model Type

CASE_CONTROL

Study Time Perspective

CROSS_SECTIONAL

Study Groups

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COPD

30 COPD participants, 16 Female and 14 Male.

COPD

Intervention Type OTHER

A vowel segmentation data set consisting of information from COPD and HC groups will be used to experiment with the classification performance of several Machine Learning techniques on different segments of a vowel recording.

HC

38 HC participants, 20 Female and 18 Male.

COPD

Intervention Type OTHER

A vowel segmentation data set consisting of information from COPD and HC groups will be used to experiment with the classification performance of several Machine Learning techniques on different segments of a vowel recording.

Interventions

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COPD

A vowel segmentation data set consisting of information from COPD and HC groups will be used to experiment with the classification performance of several Machine Learning techniques on different segments of a vowel recording.

Intervention Type OTHER