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Updated: Dec 23, 2025

Asthma Detection Research Based on Voice Signal Processing and Machine Learning
Published on: July 22, 2025
Population-based case-finding to identify subjects with undiagnosed asthma or COPD
Matthew Preteroti1, G Alex Whitmore2, Katherine L Vandemheen1
1The Ottawa Hospital Research Institute, University of Ottawa, Ottawa, ON, Canada.
Approximately 20% of Canadians with respiratory symptoms have undiagnosed asthma or COPD. Standard questionnaires are insufficient for accurate case-finding of obstructive lung disease.
Area of Science:
- Pulmonology
- Epidemiology
- Public Health
Background:
- Undiagnosed airflow obstruction, including asthma and COPD, affects an estimated 5-10% of adults.
- A population-based strategy is needed to identify undiagnosed cases among symptomatic individuals.
Purpose of the Study:
- To develop and evaluate a case-finding strategy for undiagnosed airflow obstruction (asthma or COPD) in adults with respiratory symptoms in Canada.
Main Methods:
- Recruitment of adults without prior lung disease history via random digit-dialling.
- Symptom assessment followed by validated questionnaires (ASQ, COPD-DQ, CAT) for those with symptoms.
- Pre- and post-bronchodilator spirometry for individuals scoring high on questionnaires to diagnose asthma or COPD.
Main Results:
- 20% of enrolled participants (184/910) had undiagnosed obstructive lung disease (73 asthma, 111 COPD).
- Individuals with undiagnosed disease reported more severe symptoms and lower quality of life.
- Descriptive variables (age, BMI, sex, pack-years) showed better predictive value (ROC area=0.68) than questionnaires (ROC area ≤ 0.64).
Conclusions:
- A significant proportion (20%) of symptomatic Canadians have undiagnosed asthma or COPD.
- Current screening questionnaires have limitations in accurately identifying individuals with undiagnosed obstructive lung disease.
- A combination of symptom reporting and basic demographic data may be more effective for case-finding than questionnaires alone.
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