Bionic sensing system and characterization of exhaled nitric oxide detection based on canine olfaction

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.

Structure Optimization and Data Processing Method of Electronic Nose Bionic Chamber for Detecting Ammonia Emissions from Livestock Excrement Fermentation

“…Additionally, the effect of airflow on the sensor is a critical factor [ 39 , 40 ]. Previous studies have shown that a sensor’s response is linked to the flow velocity of dynamic airflow.…”

“…These patterns are determined by the olfactory recesses located in the posterior part of the nasal cavity [36]. Based on the structure of canine olfactory-sensitive nasal cavities [37,38] and relevant studies [39], the chamber was designed to emulate a In Figure 2b, the biomimetic chamber, made from white photosensitive resin with a 0.1 mm accuracy, is created using an SLA880 device from ZRapid Tech (Suzhou, China). The chamber includes a flow guide cavity to ensure stable airflow, featuring a 30 mm inner diameter in the body portion and a 3 mm inner diameter at both the inlet and the outlet.…”

“…These patterns are determined by the olfactory recesses located in the posterior part of the nasal cavity [ 36 ]. Based on the structure of canine olfactory-sensitive nasal cavities [ 37 , 38 ] and relevant studies [ 39 ], the chamber was designed to emulate a “large chamber with a small entrance,” including a sieve plate structure. This design mirrors the distribution of olfactory cells in the nasal cavity.…”

“…Figure 3d illustrates how aging affects the sensor's baseline resistance R 0 and the resistance R S in the presence of ammonia, resulting in minor changes that can alter the response of the sensor. • Additionally, the effect of airflow on the sensor is a critical factor [39,40]. Previous studies have shown that a sensor's response is linked to the flow velocity of dynamic airflow.…”

Multivariate Regression in Conjunction with GA-BP for Optimization of Data Processing of Trace NO Gas Flow in Active Pumping Electronic Nose

“…To improve the detection accuracy of trace gases according to the concentration interval of FeNO, this study simulated the NO exhaled by the human body based on a standard sample gas, placed a NO electrochemical sensor in a bionic chamber, and adopted a pumping gas sampling method to establish a bionic-chamber-based electronic nose detection system [ 37 ]. The impact of the pump suction flow on the system’s detection accuracy was determined using ANOVA, and a multivariate regression (MR) and genetic algorithm–back propagation (GA-BP) correction method was proposed to improve the detection accuracy of the system.…”