Non-Invasive Exhaled Breath Analysis for Chronic Obstructive Pulmonary Disease Classification Using an Electronic Nose System

Chronic obstructive pulmonary disease (COPD) is a progressive lung illness involving persistent airway inflammation, primarily due to long-term inhalation of cigarette smoke. The exhaled breath of patients with COPD contains volatile organic compounds that serve as biomarkers. An electronic nose system offers a non-invasive and cost-effective approach suitable for disease detection. This study presents an electronic nose system integrated with an adaptive boosting model to distinguish COPD patients from healthy individuals through exhaled breath analysis. Experimental results indicate that the proposed system achieves an F1-score exceeding 95%, highlighting its effectiveness and potential as a reliable diagnostic tool for COPD screening.

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Publication Details

Journal
Procedia Computer Science
Published
2025-01-01
DOI
https://doi.org/10.1016/j.procs.2025.09.086
Citations
1
Primary Topic
Advanced Chemical Sensor Technologies
Type
article
Field-Weighted Citation Impact
0.67
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article

Non-Invasive Exhaled Breath Analysis for Chronic Obstructive Pulmonary Disease Classification Using an Electronic Nose System

Muhammad Rivai, Sheva Aulia, Dava Aulia, Annisa Fitria Nur
1 citations
Procedia Computer Science
Advanced Chemical Sensor Technologies
0.67
article

Non-Invasive Exhaled Breath Analysis for Chronic Obstructive Pulmonary Disease Classification Using an Electronic Nose System

Muhammad Rivai, Sheva Aulia, Dava Aulia, Annisa Fitria Nur
article en
1 citations

Abstract

Chronic obstructive pulmonary disease (COPD) is a progressive lung illness involving persistent airway inflammation, primarily due to long-term inhalation of cigarette smoke. The exhaled breath of patients with COPD contains volatile organic compounds that serve as biomarkers. An electronic nose system offers a non-invasive and cost-effective approach suitable for disease detection. This study presents an electronic nose system integrated with an adaptive boosting model to distinguish COPD patients from healthy individuals through exhaled breath analysis. Experimental results indicate that the proposed system achieves an F1-score exceeding 95%, highlighting its effectiveness and potential as a reliable diagnostic tool for COPD screening.

Procedia Computer ScienceVol. 269
Sepuluh Nopember Institute of Technology (ID), Universitas Pembangunan Nasional Veteran Jakarta (ID)
Openalex Percentile: Top 25%
Advanced Chemical Sensor Technologies
0.67
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