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

NCT05897944 | Completed DMC

• 1 other identifier: BTH-6.1.1-0074-2023
• Study Type: observational
• Target: 72
• Locations: 1 country
• Sites: 1

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.

Conditions

Chronic Obstructive Pulmonary Disease

Keywords

Automatic; Classification; COPD; Machine Learning; Mobile phone

Outcome Measures

Primary Outcomes (2)

• Accuracy

  Binary detection performance of the ML algorithm

  Week 51

• Input data importance scale

  Features used as input data will be ranked from most important to less important one.

  Week 51

Study Arms (2)

COPD

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

Other: COPD

HC

Participants without Chronic obstructive pulmonary disease diagnosis. Total 38 recruitment, 20 Female, 18 Male

Other: COPD

Interventions

COPD OTHER

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

COPD; HC

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Age Groups: Adult (18-64), Older Adult (65+)
• 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.

You may qualify if:

• being 18 years old and older.

You may not qualify if:

• being under 18 years old.

Sponsors & Collaborators

• Blekinge Institute of Technology: lead
• Excellence Center at Linköping - Lund in Information Technology (ELLIIT): collaborator

Study Sites (1)

Blekinge Institute of Technology

Karlskrona, Blekinge County, 37179, Sweden

Location

Related Publications (1)

• Idrisoglu A, Dallora AL, Cheddad A, Anderberg P, Jakobsson A, Sanmartin Berglund J. COPDVD: Automated classification of chronic obstructive pulmonary disease on a new collected and evaluated voice dataset. Artif Intell Med. 2024 Oct;156:102953. doi: 10.1016/j.artmed.2024.102953. Epub 2024 Aug 15.

  PMID: 39222579 DERIVED

MeSH Terms

Conditions

Pulmonary Disease, Chronic Obstructive

Condition Hierarchy (Ancestors)

Lung Diseases, Obstructive; Lung Diseases; Respiratory Tract Diseases; Chronic Disease; Disease Attributes; Pathologic Processes; Pathological Conditions, Signs and Symptoms

Study Officials

• Johan Sanmartin Berglund, MD, PhD

  Blekinge Institute of Technology

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: CASE CONTROL
• Time Perspective: CROSS SECTIONAL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor, MD, PhD

Study Record Dates

• First Submitted: June 1, 2023
• First Posted: June 9, 2023
• Study Start: December 16, 2021
• Primary Completion: August 12, 2024
• Study Completion: October 30, 2024
• Last Updated: March 19, 2025

Record last verified: 2025-03

Data Sharing

• IPD Sharing: Will not share

Locations

SE (1)