Creating and Assessing a Voice Dataset for Automated Classification of Chronic Obstructive Pulmonary Disease

Sponsor

Blekinge Institute of Technology (Other)

Overall Status

Active, not recruiting

CT.gov ID

NCT05897944

Collaborator

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

Enrollment

Location

24.4

Anticipated Duration (Months)

2.9

Patients Per Site Per Month

Study Details

Study Description

Brief Summary

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.

Condition or Disease	Intervention/Treatment	Phase
Chronic Obstructive Pulmonary Disease	Other: COPD

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 Design

Study Type:

Observational

Actual Enrollment :

72 participants

Observational Model:

Case-Control

Time Perspective:

Cross-Sectional

Official Title:

Creating and Assessing a Voice Dataset for Automated Classification of Chronic Obstructive Pulmonary Disease

Actual Study Start Date :

Dec 16, 2021

Actual Primary Completion Date :

May 16, 2023

Anticipated Study Completion Date :

Dec 30, 2023

Arms and Interventions

Arm	Intervention/Treatment
COPD Participants with clinically diagnosed Chronic obstructive pulmonary disease. Total 34 recruitment, 18 Female, 16 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. Other Names: HC
HC 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. Other Names: HC

Arm

Intervention/Treatment

COPD

Participants with clinically diagnosed Chronic obstructive pulmonary disease. Total 34 recruitment, 18 Female, 16 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.

Other Names:

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.

Other Names:

Outcome Measures

Primary Outcome Measures

Accuracy [Week 51]
Binary detection performance of the ML algorithm
Input data importance scale [Week 51]
Features used as input data will be ranked from most important to less important one.