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

Active, not recruiting

• Conditions: Chronic Obstructive Pulmonary Disease
• Interventions: Other: COPD

• Registration Number: NCT06160674
• Lead Sponsor: Blekinge Institute of Technology

Brief Summary

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.

Detailed Description

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.

Study Timeline

• Study Start: 2023-11-28
• Study First Submitted: 2023-11-28
• Study First Submitted QC: 2023-12-05
• Study First Posted: 2023-12-07
• Primary Completion: 2024-10-30
• Status Verified: 2024-11
• Last Update Submitted: 2024-11-22
• Last Update Posted: 2024-11-25
• Study Completion: 2024-11-30

Recruitment & Eligibility

• Status: ACTIVE_NOT_RECRUITING
• Sex: All
• Target Recruitment: 68

Inclusion Criteria

• being 18 years old and older.

Exclusion Criteria

• being under 18 years old and older.

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Arm && Interventions

Group	Intervention	Description
HC	COPD	38 HC participants, 20 Female and 18 Male.
COPD	COPD	30 COPD participants, 16 Female and 14 Male.

Primary Outcome Measures

Name	Time	Method
Classification performance	30 weeks	Binary classification performance of the ML algorithm on each segment.

Trial Locations

Locations (1)

Blekinge Institute of Technology; 🇸🇪 Karlskrona, Blekinge, Sweden