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

November 22, 2024 updated by: Blekinge Institute of Technology
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.

Study Overview

Status

Active, not recruiting

Conditions

Intervention / Treatment

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 Type

Observational

Enrollment (Actual)

68

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • Sweden
    • Blekinge
      • Karlskrona, Blekinge, Sweden, 37179
        • Blekinge Institute of Technology

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

Yes

Sampling Method

Non-Probability Sample

Study Population

Data will be collected from participants 18 years old and older with and without COPD diagnosis will be recruited.

Description

Inclusion Criteria:

  • being 18 years old and older.

Exclusion Criteria:

  • being under 18 years old and older.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
COPD
30 COPD participants, 16 Female and 14 Male.
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.
Other Names:
  • HC
HC
38 HC participants, 20 Female and 18 Male.
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.
Other Names:
  • HC

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Classification performance
Time Frame: 30 weeks
Binary classification performance of the ML algorithm on each segment.
30 weeks

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Blekinge Institute of Technology

Collaborators

Excellence Center at Linköping - Lund in Information Technology (ELLIIT)

Investigators

  • Principal Investigator: Johan Sanmartin Berglund, MD, PhD, Blekinge Institute of Technology

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

November 28, 2023

Primary Completion (Actual)

October 30, 2024

Study Completion (Estimated)

November 30, 2024

Study Registration Dates

First Submitted

November 28, 2023

First Submitted That Met QC Criteria

December 5, 2023

First Posted (Actual)

December 7, 2023

Study Record Updates

Last Update Posted (Estimated)

November 25, 2024

Last Update Submitted That Met QC Criteria

November 22, 2024

Last Verified

November 1, 2024

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • BTH-6.1.1-0169-2023

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

IPD Plan Description

Participant data can not be shared due to the GDPR. However, the dataset created can be available upon request from the institution.

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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