Research On Electronic Nose For Detection Of Halitosis And Disease Screening Based On Exhaled Gas

Halitosis refers to the unpleasant smell emitted from the mouth when breathing,which will have a serious impact on personal image and mental health.The appearance of halitosis is usually related to oral hygiene and oral diseases.Nowadays,halitosis has become the most common complaint disease except caries and periodontal diseases.Because of the cost,operation complexity and volume of commercial halitosis detection instruments,their application scope can only be limited to hospitals.Therefore,it is of great significance to design an electronic nose for halitosis marker detection and oral disease screening with personal or family use prospects.Based on this starting point,the main contents and innovations of this paper are as follows:1.A standardized method and process for the determination of volatile sulfide compounds in oral cavity by gas chromatography-mass spectrometry(GC-MS)was established.Hydrogen sulfide and methyl mercaptan as potential markers of halitosis have been gradually used in clinical evaluation of halitosis.However,due to their high reactivity and trace concentration,the analysis of VSCs in exhaled gas is challenging.In view of these difficulties,102 breath samples were collected by using Tedlar sampling bag.Based on GC-MS technology,VSCs in exhaled breath were analyzed qualitatively and quantitatively by using single ion monitoring mode and external standard method.2.The measurement results of Halimeter,Oral Chroma and GC-MS were analyzed to determine the concentration range of VSCs between different organoleptic scores and establish the diagnosis model of oral diseases.All subjects were tested by Halimeter,Oral Chroma and GC-MS.This paper analyzes the correlation between the test results of different instruments and the correlation between the test results and organoleptic scores,and uses receiver operating characteristic curve(ROC curve)to determine the concentration range of VSCs with different organoleptic scores.Taking the measurement results of GC-MS as the independent variables of the disease diagnosis model,a diagnosis model of oral diseases based on linear discriminant analysis and logistic regression method was designed,and the diagnosis effects of different models were analyzed and compared.3.Taking the measurement results of GC-MS as the reference standard of sensor screening,the software and hardware design of the electronic nose based on exhaled gas for halitosis marker detection and disease screening was completed.The concentration range of VSCs in the exhaled gas of patients with halitosis was determined from the results of GC-MS measurement.The results of GC-MS were used as the reference standard for the screening of electronic nose sensors.The electrochemical sensors with range,sensitivity,resolution and specificity in accordance with the requirements of the detection were selected as the core detection elements of electronic nose.On this basis,the air chamber and air circuit structure of sensor array are designed.The electronic nose system based on breath gas for odor detection and disease screening is developed.The influence of hardware parameters on electronic nose performance is analyzed in detail.The design of the program of electronic nose slave computer and data acquisition software of host computer are completed.4.The basic performance of the electronic nose is tested,the quantitative algorithm model of VSCs based on one-dimensional convolutional neural network is constructed,and the effect of the electronic nose in the detection of actual clinical samples is evaluated.The detection limit,repeatability and linearity of the electronic nose were tested with different concentrations of standard gases prepared by the gas distribution system.The results show that the detection limit of the electronic nose for hydrogen sulfide and methyl mercaptan are 39 ppb and 48 ppb respectively,and it has excellent repeatability and linearity.A quantitative algorithm model of VSCs based on one-dimensional convolutional neural network was constructed.27 clinical samples were collected and detected by electronic nose and GC-MS simultaneously.Compared with the results of GC-MS,the average relative error of the electronic nose in detecting VSCs in actual clinical samples was 11.7%.Taking the sensory score of olfactory discriminator as the gold standard,the electronic nose score was compared with the sensory score of olfactory discriminator,and the accuracy of the electronic nose score was 77.8%.Taking the measurement results of the electronic nose as independent variables and substituting it into the oral disease diagnosis model based on linear discriminant analysis,the sensitivity and specificity of the electronic nose to distinguish oral disease patients and healthy people were 87.5% and 72.7% respectively,and the overall accuracy rate was 81.5%.