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NCT06160674 Clinical Trial

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

Chronic Obstructive Pulmonary Disease Clinical Trial

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

Clinical Trial Details — Status: Active, not recruiting

Administrative data
NCT number NCT06160674
Other study ID # BTH-6.1.1-0169-2023
Secondary ID
Status Active, not recruiting
Phase
First received
Last updated
Start date November 28, 2023
Est. completion date August 30, 2024

Study information
Verified date November 2023
Source Blekinge Institute of Technology
Contact n/a
Is FDA regulated No
Health authority
Study type Observational [Patient Registry]

Clinical Trial 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.

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.

Recruitment information / eligibility
Status Active, not recruiting
Enrollment 68
Est. completion date August 30, 2024
Est. primary completion date May 30, 2024
Accepts healthy volunteers Accepts Healthy Volunteers
Gender All
Age group 18 Years and older
Eligibility Inclusion Criteria: - being 18 years old and older. Exclusion Criteria: - being under 18 years old and older.

Study Design

Related Conditions & MeSH terms

Intervention

Other:
• 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.

Locations
Country Name City State
Sweden Blekinge Institute of Technology Karlskrona Blekinge

Sponsors (2)
Lead Sponsor Collaborator
Blekinge Institute of Technology Excellence Center at Linköping - Lund in Information Technology (ELLIIT)

Country where clinical trial is conducted

Sweden, 

Outcome
Type Measure Description Time frame Safety issue
Primary Classification performance Binary classification performance of the ML algorithm on each segment. 30 weeks
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