Application of a Piezoelectric Nose to Assessing the Respiratory System in Calves by Volatile Compounds

Кучменко, Т. А.; Шуба, А. А.; Умарханов, Р. У.; Drozdova, E. V.; Черницкий, А. Е.

doi:10.1134/s1061934820050093

Cited by 6 publications

(8 citation statements)

References 15 publications

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“…Frequently, these factors act together, which makes it difficult to estimate and predict the contribution of an individual factor to the total signal change. The other internal factors, such as the malfunctions in the oscillating scheme of the device and the change in the features of utilized quartz and electrodes, and the problems linked to signal transmission into software for our devices, lead to no more than 5% variation in sensor signals [19]. The algorithm of multivariate data processing for the drift compensation of the sensor signals was limited by the pilot experiment conditions for the model design.…”

Section: Resultsmentioning

confidence: 99%

Drift Compensation of the Electronic Nose in the Development of Instruments for Out-of-Laboratory Analysis

Шуба

Кучменко

Menzhulina³

2022

The 1st International Electronic Conference on Chemical Sensors and Analytical Chemistry

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A technique was developed to evaluate and compensate for the drift of eight mass-sensitive sensors in an open detection cell in order to estimate the influence of external factors (temperature, changes in the chemical composition of the background) on the out-of-laboratory analysis of biosamples. The daily internal standardization of the system is an effective way to compensate for the sensor signal drift when the sorption properties of sensitive coatings change during their long-term, intensive operation. In this study, distilled water was proposed as a standard for water matrix-based biosamples (blood, exhaled breath condensate, urine, etc.). Further, internal standardization was based on daily calculation of the specific sensor signals by dividing the sensor signals for the biosample according to the corresponding averaged values obtained from three to five standard measurements. The stability of the sensor array operation was estimated using the theory of statistical process control (exponentially weighted moving average control charts) based on the specific signal of the sensor array. The control limits for the statistical quantity of the central tendency for each sensor and the whole array, as well as the variations of the sensor signals, were determined. The average times required for signal and run lengths, for the purpose of statistically substantiated monitoring of the electronic nose’s stability, were calculated. Based on an analysis of the tendency and variations in sensor signals during 3 months of operation, a technique was formulated to control the stability of the sensor array for the out-of-laboratory analysis of the biosamples. This approach was successfully verified by classifying the results of the analysis of the blood and water samples obtained for this period. The proposed technique can be introduced into the software algorithm of the electronic nose, which will improve decision-making during the long-term monitoring of health conditions in humans and animals.

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Section: Resultsmentioning

confidence: 99%

Drift Compensation of the Electronic Nose in the Development of Instruments for Out-of-Laboratory Analysis

Шуба

Кучменко

Menzhulina³

2022

The 1st International Electronic Conference on Chemical Sensors and Analytical Chemistry

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“…The loading plot ( Figure 8 ) shows that the initial signals made the most considerable contribution to the model of the sensors ΔF max,i , and the signals from the first set of sensors were more significant than from the second set. Therefore, taking into account the loadings for the seven principal components of the PCA–LDA model (shown in Table 6 , Figure 8 ), the most significant for classification were the signals of sensors with modifiers of carboxylated carbon nanotubes, zirconium nitrate, hydroxyapatite, methyl orange, bromocresol green, Triton X-100, and polyethylene glycol and its ethers, which are highly sensitive to vapors of nitrogen- and oxygen-containing compounds according to our previous investigation of sorption features of VOCs on these sorbents [ 37 , 51 , 52 , 53 , 54 , 55 , 56 , 57 ].…”

Section: Discussionmentioning

confidence: 99%

“…These sorbents were chosen among 50 phases due to them having hypersensitivity to various classes of highly volatile organic compounds (alcohols, aldehydes, acids, ketones, amines, and arenes) [ 36 , 37 , 51 , 52 , 53 , 54 , 55 , 56 , 57 ], including volatile biomarkers of respiratory pathologies.…”

Section: Methodsmentioning

confidence: 99%

“…The most perspective direction in BRD diagnosis using metabolomics involves noninvasive methods when researching the metabolic profiles of exhaled breath gas [ 34 ], exhaled breath condensate [ 35 ], and nasal secretions [ 28 , 36 ]. One of such diagnostic methods is the analysis of the composition of the gaseous phases of biological samples (exhaled breath condensate, nasal secretions) using an array of piezoelectric sensors with the methodology of an “electronic nose” (e-nose) [ 36 , 37 ]. Traditionally, the determination of BRD volatile markers in the gas phase over biological samples using an e-nose is carried out on the basis of sensor signals using pattern recognition algorithms or multivariate regression.…”

Section: Introductionmentioning

confidence: 99%

“…The whole set of substances is evaluated as an integral indicator of the biological sample condition [ 38 , 39 , 40 , 41 ]. An alternative approach to processing the sensor array data in the analysis of biological samples is also possible, based on calculating the sorption efficiency parameters A i/j [ 37 , 42 , 43 ], which mainly reflect the qualitative composition of the gas mixture and can be further processed by various mathematical algorithms.…”

Section: Introductionmentioning

confidence: 99%

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Portable Electronic Nose for Analyzing the Smell of Nasal Secretions in Calves: Toward Noninvasive Diagnosis of Infectious Bronchopneumonia

Кучменко

Шуба

Умарханов

et al. 2021

Veterinary Sciences

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The paper demonstrates a new approach to identify healthy calves (“healthy”) and naturally occurring infectious bronchopneumonia (“sick”) calves by analysis of the gaseous phase over nasal secretions using 16 piezoelectric sensors in two portable devices. Samples of nasal secretions were obtained from 50 red-motley Holstein calves aged 14–42 days. Calves were subjected to rectal temperature measurements, clinical score according to the Wisconsin respiratory scoring chart, thoracic auscultation, and radiography (Carestream DR, New York, USA). Of the 50 calves, we included samples from 40 (20 “healthy” and 20 “sick”) in the training sample. The remaining ten calves (five “healthy” and five “sick”) were included in the test sample. It was possible to divide calves into “healthy” and “sick” groups according to the output data of the sensor arrays (maximum sensor signals and calculated parameters Ai/j) using the principal component linear discriminant analysis (PCA–LDA) with an accuracy of 100%. The adequacy of the PCA–LDA model was verified on a test sample. It was found that data of sensors with films of carbon nanotubes, zirconium nitrate, hydroxyapatite, methyl orange, bromocresol green, and Triton X-100 had the most significance for dividing samples into groups. The differences in the composition of the gaseous phase over the samples of nasal secretions for such a classification could be explained by the appearance or change in the concentrations of ketones, alcohols, organic carboxylic acids, aldehydes, amines, including cyclic amines or those with a branched hydrocarbon chain.

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Application of piezoelectric e-noses for diagnostics of animal and human health

Кучменко¹,

Шуба²

2023

Nanotechnology-Based E-Noses

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Application of a Piezoelectric Nose to Assessing the Respiratory System in Calves by Volatile Compounds

Cited by 6 publications

References 15 publications

Drift Compensation of the Electronic Nose in the Development of Instruments for Out-of-Laboratory Analysis

Drift Compensation of the Electronic Nose in the Development of Instruments for Out-of-Laboratory Analysis

Portable Electronic Nose for Analyzing the Smell of Nasal Secretions in Calves: Toward Noninvasive Diagnosis of Infectious Bronchopneumonia

Application of piezoelectric e-noses for diagnostics of animal and human health

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