Electronic nose dataset for COPD detection from smokers and healthy people through exhaled breath analysis

Cristhian Manuel Durán Acevedo; Carlos A Cuastumal Vasquez; Jeniffer Katerine Carrillo Gómez

doi:10.1016/j.dib.2021.106767

Electronic nose dataset for COPD detection from smokers and healthy people through exhaled breath analysis

Data Brief. 2021 Jan 18:35:106767. doi: 10.1016/j.dib.2021.106767. eCollection 2021 Apr.

Authors

Cristhian Manuel Durán Acevedo¹, Carlos A Cuastumal Vasquez¹, Jeniffer Katerine Carrillo Gómez¹

Affiliation

¹ Multisensor systems and pattern recognition research group, University of Pamplona, North of Santander, Pamplona, Colombia.

Abstract

This article presents a database which was obtained by acquiring measurements through a multisensory device called Electronic Nose (E-nose) based on a matrix of metal oxide sensors, in order to discriminate and classify a group of people affected by the respiratory disease Chronic Obstructive Pulmonary Disease (COPD), smokers and healthy control people through exhaled breath analysis. The database consists of 4 groups of measurements which were acquired through the E-nose system: 10 control samples (healthy people), 20 samples of people with COPD, 4 samples of smokers and 10 air samples, where in each group two samples of exhaled breath per person were acquired giving a total of 78 samples (40 from COPD, 20 from control, 8 from smokers and 10 from the air).

Keywords: COPD; Electronic nose; Exhaled breath; Gas sensor; Machine learning.