An ADC-free adaptive interface circuit of resistive sensor for electronic nose system

More effective methods to detect bovine tuberculosis, caused by Mycobacterium bovis, in wildlife, is of paramount importance for preventing disease spread to other wild animals, livestock, and human beings. In this study, we analyzed the volatile organic compounds emitted by fecal samples collected from free-ranging wild boar captured in Doñana National Park, Spain, with an electronic nose system based on organically-functionalized gold nanoparticles. The animals were separated by the age group for performing the analysis. Adult (>24 months) and sub-adult (12–24 months) animals were anesthetized before sample collection, whereas the juvenile (<12 months) animals were manually restrained while collecting the sample. Good accuracy was obtained for the adult and sub-adult classification models: 100% during the training phase and 88.9% during the testing phase for the adult animals, and 100% during both the training and testing phase for the sub-adult animals, respectively. The results obtained could be important for the further development of a non-invasive and less expensive detection method of bovine tuberculosis in wildlife populations.

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A Weighted Discriminative Extreme Learning Machine Design for Lung Cancer Detection by an Electronic Nose System

IEEE Transactions on Instrumentation and Measurement ◽

10.1109/tim.2021.3084312 ◽

2021 ◽

pp. 1-1

Author(s):

Leilei Zhao ◽

Junhui Qian ◽

Fengchun Tian ◽

Ran Liu ◽

Bei Liua ◽

...

Keyword(s):

Lung Cancer ◽

Extreme Learning Machine ◽

Cancer Detection ◽

Electronic Nose ◽

Machine Design ◽

Learning Machine ◽

Electronic Nose System ◽

Lung Cancer Detection

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A High performance electronic nose system for the recognition of myocardial infarction and coronary artery diseases

Biomedical Signal Processing and Control ◽

10.1016/j.bspc.2020.102247 ◽

2021 ◽

Vol 64 ◽

pp. 102247

Author(s):

Bilge Han Tozlu ◽

Cemaleddin Şimşek ◽

Onder Aydemir ◽

Yusuf Karavelioglu

Keyword(s):

Myocardial Infarction ◽

Coronary Artery ◽

Electronic Nose ◽

High Performance ◽

Coronary Artery Diseases ◽

Electronic Nose System

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Methods for Improving an Electronic Nose System to Detect Urinary Tract Infection

10.31979/etd.tdmg-9wgr ◽

2020 ◽

Author(s):

Nam T Than

Keyword(s):

Urinary Tract Infection ◽

Urinary Tract ◽

Tract Infection ◽

Electronic Nose ◽

Electronic Nose System

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Discrimination between Alternative Herbal Medicines from Different Categories with the Electronic Nose

Sensors ◽

10.3390/s18092936 ◽

2018 ◽

Vol 18 (9) ◽

pp. 2936 ◽

Cited By ~ 6

Author(s):

Xianghao Zhan ◽

Xiaoqing Guan ◽

Rumeng Wu ◽

Zhan Wang ◽

You Wang ◽

...

Keyword(s):

Herbal Medicine ◽

Electronic Nose ◽

Nearest Neighbor ◽

Herbal Medicines ◽

Principal Component ◽

Support Vector ◽

Linear Discriminant ◽

Convenient Means ◽

Electronic Nose System ◽

Insight Into

As alternative herbal medicine gains soar in popularity around the world, it is necessary to apply a fast and convenient means for classifying and evaluating herbal medicines. In this work, an electronic nose system with seven classification algorithms is used to discriminate between 12 categories of herbal medicines. The results show that these herbal medicines can be successfully classified, with support vector machine (SVM) and linear discriminant analysis (LDA) outperforming other algorithms in terms of accuracy. When principal component analysis (PCA) is used to lower the number of dimensions, the time cost for classification can be reduced while the data is visualized. Afterwards, conformal predictions based on 1NN (1-Nearest Neighbor) and 3NN (3-Nearest Neighbor) (CP-1NN and CP-3NN) are introduced. CP-1NN and CP-3NN provide additional, yet significant and reliable, information by giving the confidence and credibility associated with each prediction without sacrificing of accuracy. This research provides insight into the construction of a herbal medicine flavor library and gives methods and reference for future works.

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