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

被引:16
作者
Acevedo, Cristhian Manuel Duran [1 ]
Vasquez, Carlos A. Cuastumal [1 ]
Gomez, Jeniffer Katerine Carrillo [1 ]
机构
[1] Univ Pamplona, Multisensor Syst & Pattern Recognit Res Grp, Pamplona, Colombia
关键词
Electronic nose; Exhaled breath; COPD; Gas sensor; Machine learning;
D O I
10.1016/j.dib.2021.106767
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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) (C) 2021 The Authors. Published by Elsevier Inc.
引用
收藏
页数:6
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