ArticlePloS one2022
Bionic sensing system and characterization of exhaled nitric oxide detection based on canine olfaction.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- Structure Optimization and Data Processing Method of Electronic Nose Bionic Chamber for Detecting Ammonia Emissions from Livestock Excrement Fermentation.Sensors (Basel, Switzerland) · 2024Article
- Article
- Multivariate Regression in Conjunction with GA-BP for Optimization of Data Processing of Trace NO Gas Flow in Active Pumping Electronic Nose.Sensors (Basel, Switzerland) · 2023Article
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3 authors at 1 institution in 1 country.
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Abstract
A quantitative monitoring system for fractional exhaled nitric oxide (FENO) in homes is very important for the control of respiratory diseases such as asthma. To this end, this paper proposes a small bionic sensing system for NO detection in an electronic nose based on analysis of the structure of the canine olfactory system and the airflow pattern in the nasal cavity. The proposed system detected NO at different FENO concentration levels with different bionic sensing systems in the electronic nose, and analyzed the data comparatively. Combined with a backpropagation neural network algorithm, the bionic canine sensing system improved the recognition rate for FENO detection by up to 98.1%. Moreover, electronic noses with a canine bionic sensing system can improve the performance of trace gas detection.
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