An observational study in Chronic Obstructive Pulmonary Disease, sponsored by Blekinge Institute of Technology. Completed at 1 site in Sweden. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2025-03-19.
Sponsored by Blekinge Institute of Technology · Observational
This work aims to evaluate whether voice recordings collected from patients diagnosed with COPD and healthy control groups can be used to detect the disease using machine learning techniques.
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.
5,520 studies on the registry are indexed under Pulmonary Disease, Chronic Obstructive; 856 are open to participants now.
This study's enrollment of 72 is below the median of 158 across 1,497 observational studies indexed under Pulmonary Disease, Chronic Obstructive.
Browse Pulmonary Disease, Chronic Obstructive studies →Blekinge Institute of Technology is the lead sponsor of 14 studies on the registry; 6 are open to participants now.
Counted across the registry records on this site, refreshed daily.
Data will be collected from participants 18 years old and older with and without COPD diagnosis will be recruited.
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Exclusion Criteria:
Participants with clinically diagnosed Chronic obstructive pulmonary disease. Total 34 recruitment, 18 Female, 16 Male
Other: COPD
Participants without Chronic obstructive pulmonary disease diagnosis. Total 38 recruitment, 20 Female, 18 Male
Other: COPD
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.
Also known as: HC
Accuracy
Binary detection performance of the ML algorithm
Time frame: Week 51
Input data importance scale
Features used as input data will be ranked from most important to less important one.
Time frame: Week 51
Plan to share: No — Participant data can not be shared due to the GDPR. However, the dataset created can be available upon request from the institution.
No publications or documents are linked to this record.
Ran from Dec 2021 to primary completion in Aug 2024, 31 months.
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This study is completed, as verified in Mar 2025. You cannot join it, but the record below documents what was studied.
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Pulmonary Disease, Chronic Obstructive →
Blekinge Institute of Technology