- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT05897944
Creating and Assessing a Voice Dataset for Automated Classification of Chronic Obstructive Pulmonary Disease
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, which allows one to participate without location dependency. Participants with a diagnosis will be marked as the COPD group, and others will be marked as the healthy control group. Private information such as known comorbidities, personal security numbers, health parameters and communication information will be separately noticed in a participation table for each group.
The collected data 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 further usage as an input to ML techniques.
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.
Study Plan
How is the study designed?
Design Details
Cohorts and Interventions
Group / Cohort |
Intervention / Treatment |
---|---|
COPD
Participants with clinically diagnosed Chronic obstructive pulmonary disease.
Total 34 recruitment, 18 Female, 16 Male
|
A data set consisting of information from COPD and HC groups will be used to experiment with the classification performance of several Machine Learning techniques.
Other Names:
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HC
Participants without Chronic obstructive pulmonary disease diagnosis.
Total 38 recruitment, 20 Female, 18 Male
|
A data set consisting of information from COPD and HC groups will be used to experiment with the classification performance of several Machine Learning techniques.
Other Names:
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
---|---|---|
Accuracy
Time Frame: Week 51
|
Binary detection performance of the ML algorithm
|
Week 51
|
Input data importance scale
Time Frame: Week 51
|
Features used as input data will be ranked from most important to less important one.
|
Week 51
|
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 (Actual)
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
Additional Relevant MeSH Terms
Other Study ID Numbers
- BTH-6.1.1-0074-2023
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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