- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT06160674
Vowel Segmentation for Classification of Chronic Obstructive Pulmonary Disease Using Machine Learning
Study Overview
Status
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
Enrollment (Actual)
Contacts and Locations
Study Locations
-
-
Blekinge
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Karlskrona, Blekinge, Sweden, 37179
- Blekinge Institute of Technology
-
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Participation Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- being 18 years old and older.
Exclusion Criteria:
- being under 18 years old and older.
Study Plan
How is the study designed?
Design Details
Cohorts and Interventions
Group / Cohort |
Intervention / Treatment |
---|---|
COPD
30 COPD participants, 16 Female and 14 Male.
|
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
38 HC participants, 20 Female and 18 Male.
|
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:
|
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
Sponsor
Investigators
- Principal Investigator: Johan Sanmartin Berglund, MD, PhD, Blekinge Institute of Technology
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Estimated)
Study Completion (Estimated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
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)?
IPD Plan Description
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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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