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array optimization Based on Weighted and Hilbert-Schmidt Schemes of Multisensor Detection System

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2023年第5期19卷 7044-7054页

作者： Qian, Junhui Lu, Mengchen Tian, Fengchun Zhao, Leilei Zhang, Ailing Chongqing Univ Sch Microelect & Commun Engn Chongqing 400044 Peoples R China CETC Acad Chips Technol Beijing Peoples R China Chongqing Univ Chongqing Key Lab Biopercept & Intelligent Informa Chongqing 400044 Peoples R China

This article presents a novel sensor array optimization scheme for multisensor electronic nose detection system. A system architecture with multisensor is first proposed to implement the medical detection, including the bacterial culture medium detection and animal wound infection detection. The system efficiency is evaluated by comparing with the field asymmetric ion mobility spectrometry (FAIMS) system. To further improve the detection effect and reduce the number of sensors of the electronic nose system, we then derive two sensor array optimization procedures based on factor analysis and Hilbert-Schmidt independence criterion, respectively. Specifically, the weighted factor analysis method and nonweighted factor analysis method are proposed via factor analysis. Besides, the Hilbert-Schmidt independence criterion optimization design of linear kernel function and Gaussian kernel function are also exploited. The experimental results highlight that compared with the existing approaches, the proposed weighted factor analysis optimization method and Hilbert-Schmidt independence criterion optimization method (Gaussian kernel function) can achieve a significant system performance.

关键词： Wounds Microorganisms sensor arrays Animals Hydrogen Methane Liquids Electronic nose (E-nose) factor analysis (FA) Hilbert-Schmidt independence criterion (HSIC) sensor array optimization

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Efficient Multifeature Extraction and Embedded array optimization for Drift-Calibrated Multisensor Odor Detection System

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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2024年 73卷 1页

作者： Qian, Junhui Xu, Peng Sun, Zhuoran Liang, Yezong Qian, Guobing Wang, Shiyuan Chongqing Univ Sch Microelect & Commun Engn Chongqing Key Lab Biopercept & Intelligent Informa Chongqing 400044 Peoples R China Jianghuai Adv Technol Ctr Hefei 230000 Peoples R China Chongqing Univ Sch Microelect & Commun Engn Chongqing 400044 Peoples R China Southwest Univ Coll Elect & Informat Engn Chongqing 400715 Peoples R China

This article focuses on achieving a reliable identification of herbal medicine while minimizing the impact of sensor drift. Therefore, 21 metal oxide sensors are implemented as sensitive units during the initial construction of the sensor array. Based on this, to fully exploit odor data and reduce computational burdens, we propose a weighted feature combination selection strategy that evaluates a feature set based on both label relevance and feature stability. To further enhance the long-term stability of the system and reduce the number of sensors, we introduce a combined scheme involving drift calibration and array optimization design. Specifically, we optimize a subspace projection matrix that considers minimizing the maximum mean discrepancy (MMD), preserving the Laplace manifold for the source domain, and maximizing the correlation coefficient between the source and target domains to compensate for sensor drift. Subsequently, we develop sensor array optimization using an embedded composition of feature relevancy (CFR) framework to eliminate redundant information in the target domain. Experimental results demonstrate that, compared to existing approaches, the proposed calibration framework achieves the best system performance with the minimum number of sensors.

关键词： Detection system feature combination selection sensor array calibration sensor array optimization

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Development an electronic nose to recognize pesticides in groundwater

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TALANTA 2024年 269卷 125506页

作者： Wang, Bingyang Chen, Donghui Weng, Xiaohui Chang, Zhiyong Jilin Univ Key Lab Bion Engn Minist Educ Changchun 130022 Peoples R China Jilin Univ Coll Biol & Agr Engn Changchun 130022 Peoples R China Jilin Univ Weihai Inst Bion Weihai 264401 Peoples R China Jilin Univ Sch Mech & Aerosp Engn Changchun 130022 Peoples R China

Timely detection of Groundwater pollution is essential to protect human health, especially for pesticide pollution. To solve this issue, we proposed a novel solution to realize the prediction of pesticide in groundwater by using the electronic nose (e-nose). The main work of this paper was divided into three steps: 1) checking whether sample was polluted by pesticides, 2) further predicting the pesticide type, brand and pollution degree when the sample was polluted by pesticides, and 3) optimizing the sensor array. Random forest was used to complete the first step, which had the best accuracy and sensitivity of 100 %. Support vector machine was applied to complete the second step, and the accuracy reaching 98.08 %. As for the third step, recursive feature elimination was used to optimize the sensor array. After optimization, the number of sensors was reduced from 26 to 8. In addition, the e-nose developed in this paper was compared with a commercial e-nose. The results showed that the cost of the developed e-nose was much lower than that of the commercial e-nose despite its slightly weaker prediction performance. Thus, this e-nose can be employed to recognize the pesticides in groundwater, and even can be integrated into the while drilling technology to realize the in-situ detection of groundwater.

关键词： Electronic nose Groundwater Pesticides sensor array optimization

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sensor Selection for an Electronic Tongue for the Rapid Detection of Paralytic Shellfish Toxins: A Case Study

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CHEMOsensorS 2024年第6期12卷 115页

作者： Raposo, Mariana Gomes, Maria Teresa S. R. Costa, Sara T. Botelho, Maria Joao Rudnitskaya, Alisa Univ Aveiro CESAM P-3810193 Aveiro Portugal Univ Aveiro Chem Dept P-3810193 Aveiro Portugal IPMA Portuguese Inst Sea & Atmosphere P-1449006 Lisbon Portugal Univ Porto Interdisciplinary Ctr Marine & Environm Res CIIMAR P-4050123 Porto Portugal Univ Porto Abel Salazar Biomed Sci Inst ICBAS Largo Prof Abel Salazar 2 P-4099003 Porto Portugal

The performance of an electronic tongue can be optimized by varying the number and types of sensors in the array and by employing data-processing methods. sensor selection is typically performed empirically, with sensors picked up either by analyzing their characteristics or through trial and error, which does not guarantee an optimized sensor array composition. This study focuses on developing a method for sensor selection for an electronic tongue using simulated sensor data and Lasso regularization. Simulated sensor responses were calculated using sensor parameters such as sensitivity and selectivity, which were determined in the individual analyte solutions. sensor selection was carried out using Lasso regularization, which removes redundant or highly correlated variables without much loss of information. The objective of the optimization of the sensor array was twofold, aiming to minimize both quantification errors and the number of sensors in the array. The quantification of toxins belonging to one of the groups of marine toxins-paralytic shellfish toxins (PSTs)-using arrays of potentiometric chemical sensors was used as a case study. Eight PSTs corresponding to the toxin profiles in bivalves due to the two common toxin-producing phytoplankton species, G. catenatum (dcSTX, GTX5, GTX6, and C1+2) and A. minitum (STX, GTX2+3), as well as total sample toxicity, were included in the study. Experimental validation with mixed solutions of two groups of toxins confirmed the suitability of the proposed method of sensor array optimization with better performance obtained for the a priori optimized sensor arrays. The results indicate that the use of simulated sensor responses and Lasso regularization is a rapid and efficient method for the selection of an optimized sensor array.

关键词： electronic tongue potentiometric sensors paralytic shellfish toxins sensor array optimization Lasso regularization

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Towards the Non-Zero Field Cesium Magnetic sensor array for Magnetoencephalography

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IEEE sensorS JOURNAL 2021年第17期21卷 18626-18632页

作者： Petrenko, Mikhail V. Dmitriev, Sergei P. Pazgalev, Anatoly S. Ossadtchi, Alex E. Vershovskii, Anton K. Ioffe Inst St Petersburg 194021 Russia Natl Res Univ Higher Sch Econ Ctr Bioelect Interfaces Moscow 101000 Russia

Magnetic sensors developed for application in magnetoencephalography must meet a number of requirements;the main ones are compactness, sensitivity and response speed. We present a quantum optically pumped atomic sensor with cell volume of 0.5 cm(3) that meets these requirements and is operable in nonzero magnetic fields. The ultimate sensitivity of the sensor was estimated as (using the criteria of the ratio of the slope of the magnetic resonance signal to the shot noise spectral density) to be better than 5 fT/root Hz. The actual sensitivity, measured in a gradiometric scheme, reaches 13 fT/root Hz per sensor. We also present a novel and fast algorithm for optimization of the geometric properties of non-zero field sensor array with respect to maximization of the information transfer rate for cortical sources.

关键词： Magnetoencephalographic sensor optically pumped magnetometer non-zero magnetic field sensor two-beam scheme sensor array optimization MEG forward model sensor lead field mutual information

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Enhancement of array optimization Algorithm via Information Theory for a Novel Multisensor Detection System

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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2023年 72卷 1页

作者： Qian, Junhui Lu, Yuanyuan Lu, Mengchen Liu, Ziyu Xu, Peng Chongqing Univ Sch Microelect & Commun Engn Chongqing 400044 Peoples R China Chongqing Univ Chongqing Key Lab Biopercept & Intelligent Informa Chongqing 400044 Peoples R China CETC Acad Chips Technol Chongqing 401332 Peoples R China

This article develops a low-cost dual-input multisensor odor detection system relying on sensor detection technology and the changing characteristics of the odor itself. The finite element analysis method is used to investigate the gas chamber, and the uniformity and stability of the flow field distribution under the wide range of flow velocity are verified through simulation results and actual verification experiments. To cope with the interference brought by redundant information, improve the system's detection accuracy, and reduce the number of sensors, we propose a sensor array optimization algorithm based on information theory. Specifically, according to the dynamic changes in the information contained in the sensor array during the optimization process, we develop a modified mutual information optimization (MMIO) framework. Experiment results show that the proposed MMIO can obtain significant system performance compared with the existing methods.

关键词： Finite element analysis modified mutual information optimization (MMIO) multisensor odor detection system sensor array optimization

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Magnetic Target Localization Correction Based on Variance Weight Distribution of Eigenvalue

Magnetic Target Localization Correction Based on Variance We...

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IEEE International Magnetic Conference (INTERMAG)

作者： Xie, D. Qiu, J. Ou, J. D. Wang, Z. Du, J. Z. Xu, Q. Chongqing Univ Key Lab Optoelect & Syst Minist Educ Coll Optoelect Engn Chongqing 400044 Peoples R China

ISBN: (纸本)9780738130996

Magnetic target localization has high application value in the fields of underwater target detection and mineral exploration. To address the problems of limited detection range and blind area of single-point detection method, the detection and positioning method based on the weight distribution correction algorithm is proposed. By designing an algorithm that combines the characteristics of the magnetic field gradient matrix to optimize the distribution of the detection array, the precise regional localization of the target is achieved. Firstly, based on the detection range and the characteristics of the obstacle area, the multi-point detection array is analyzed and the weight distribution correction model is established, then the feasibility of the positioning method is analyzed using experiment data, and finally the detection system is built to conduct positioning experiments on specific target. The results show that the multi-point weight distribution correction localization method can effectively obtain the target location information, and the detection accuracy is improved to a certain extent.

关键词： Magnetic anomaly target localization sensor array optimization particle swarm algorithm Detection reliability weight distribution

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A PSO-SVM Method for Parameters and sensor array optimization in Wound Infection Detection based on Electronic Nose

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JOURNAL OF COMPUTERS 2012年第11期7卷 2663-2670页

作者： Yan, Jia Tian, Fengchun Feng, Jingwei Jia, Pengfei He, Qinghua Shen, Yue Chongqing Univ Coll Commun Engn Chongqing Peoples R China Third Mil Med Univ Inst Surg Res Daping Hosp State Key Lab Trauma Burns & Combined Injury Chongqing Peoples R China

In this paper a new method based on the support vector machine (SVM) combined with particle swarm optimization (PSO) is proposed to analyze signals of wound infection detection based on electronic nose (enose). Owing to the strong impact of sensor array optimization and SVM parameters selection on the classification accuracy of SVM, PSO is used to realize a synchronization optimization of sensor array and SVM model parameters. The results show that PSO-SVM method combined with sensor array optimization greatly improves the classification accuracy of mice wound infection compared with radical basis function (RBF) network and genetic algorithms (GA) with/without sensor array optimization. Meanwhile, the proposed sensor array optimization method which weights sensor signals by importance factors also obtain better classification accuracy than that of weighting sensor signals by 0 and 1.

关键词： Electronic nose Wound infection Support vector machine Particle swarm optimization sensor array optimization Parameters optimization

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Molecularly Imprinted Sol-Gel-Based QCM sensor arrays for the Detection and Recognition of Volatile Aldehydes

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sensorS 2017年第2期17卷 382页

作者： Liu, Chuanjun Wyszynski, Bartosz Yatabe, Rui Hayashi, Kenshi Toko, Kiyoshi Kyushu Univ Res & Dev Ctr Taste & Odor Sensing Nishi Ku 744 Motooka Fukuoka 8190395 Japan Kyushu Univ Grad Sch Informat Sci & Elect Engn Nishi Ku 744 Motooka Fukuoka 8190395 Japan

The detection and recognition of metabolically derived aldehydes, which have been identified as important products of oxidative stress and biomarkers of cancers;are considered as an effective approach for early cancer detection as well as health status monitoring. Quartz crystal microbalance (QCM) sensor arrays based on molecularly imprinted sol-gel (MISG) materials were developed in this work for highly sensitive detection and highly selective recognition of typical aldehyde vapors including hexanal (HAL);nonanal (NAL) and bezaldehyde (BAL). The MISGs were prepared by a sol-gel procedure using two matrix precursors: tetraethyl orthosilicate (TEOS) and tetrabutoxytitanium(TBOT). Aminopropyltriethoxysilane (APT);diethylaminopropyltrimethoxysilane (EAP) and trimethoxy-phenylsilane (TMP) were added as functional monomers to adjust the imprinting effect of the matrix. Hexanoic acid (HA);nonanoic acid (NA) and benzoic acid (BA) were used as psuedotemplates in view of their analogous structure to the target molecules as well as the strong hydrogen-bonding interaction with the matrix. Totally 13 types of MISGs with different components were prepared and coated on QCM electrodes by spin coating. Their sensing characters towards the three aldehyde vapors with different concentrations were investigated qualitatively. The results demonstrated that the response of individual sensors to each target strongly depended on the matrix precursors;functional monomers and template molecules. An optimization of the 13 MISG materials was carried out based on statistical analysis such as principle component analysis (PCA);multivariate analysis of covariance (MANCOVA) and hierarchical cluster analysis (HCA). The optimized sensor array consisting of five channels showed a high discrimination ability on the aldehyde vapors;which was confirmed by quantitative comparison with a randomly selected array. It was suggested that both the molecularly imprinting (MIP) effect and the matrix effect cont

关键词： molecularly imprinted sol-gel QCM sensor array aldehyde biomarker sensor array optimization

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A sensor array optimization method for electronic noses with sub-arrays

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sensorS AND ACTUATORS B-CHEMICAL 2009年第1期142卷 243-252页

作者： Zhang, Shunping Xie, Changsheng Zeng, Dawen Li, Huayao Liu, Yuan Cai, Shuizhou Huazhong Univ Sci & Technol Nanomat & Smart Sensor Res Lab Dept Mat Sci & Engn Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol State Key Lab Mat Proc & Die & Mould Technol Wuhan 430074 Peoples R China

sensor array configuration needs to be optimized in developing an application-specific instrument of electronic noses. Currently, sensor array optimization is commonly done by feature selection techniques. These methods could solve how to optimize a sensor array. However, they could not figure out what are the unique functions that each sensor plays in the optimized sensor array. The method proposed in this paper could solve this problem by sensor clustering and dividing the whole sample classification mission into several small recognition tasks. A measurement with a six Taguchi Gas sensors (TGS sensor hereinafter) sensors array to classify 11 gas sorts was used in the data validation. The sensor array was optimized to three sensors with the proposed method. Each sensor in the optimized array had unique functions to solve different recognition tasks. TGS2600 had the unique functions to discriminate butanone and acetaldehyde. TGS2602 had the unique functions to discriminate benzene and cyclohexane, methanol and ethanol. TGS813 had the unique functions to discriminate cyclohexane and pentane. The combination of TGS2600 and TGS2602 had the unique functions to discriminate acetone and butanone, acetone and acetaldehyde. The proposed method might be a new generation of sensor array optimization methods. (C) 2009 Elsevier B. V. All rights reserved.

关键词： sensor array optimization Sub-array Electronic nose Selectivity similarity

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