• Journal of Sensor Science and Technology
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• v.20 no.6
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• pp.428-433
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• 2011

We report on the building of a micro sensor array based on typical semiconductor fabrication processes aimed at monitoring selectively a specific gas in ambient of other gases. Chemical sensors can be applied for an electronic nose and/or robots using this technique. Microsensor array was fabricated on the same chip using 0.6${\mu}m$ CMOS technology, and unique gas sensing patterns were obtained by principal component analysis from the array. $SnO_2$/Pt sensor for CO gas showed a high selectivity to buthane gas and humidity. $SnO_2$ sensor for hydrogen gas, however, showed a low selectivity to CO and buthane gas. We can obtain more distinguishable patterns that provide the small sensing deviation(the high seletivity) toward a given analyte in the response space than in the chemical space through the specific parameterization of raw data for chemical image formation.

• Journal of Sensor Science and Technology
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• v.24 no.4
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• pp.258-263
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• 2015

In order to prevent drink-driving by detecting concentration of alcohol from driver's exhale breath, twenty chemical sensors fabricated. The one of purposes for sensor array which consists of those sensors is to discriminate between target gas(alcohol) and interference gases($CH_3CH_2OH$, CO, NOx, Toluene, and Xylene). Wilks's lambda was presented to achieve above purpose and optimal sensors were selected using the method. In this paper, step-wise sensor elimination based on Euclidean distance was investigated for selecting optimal sensors and compared with a result of Wilks's lambda method. The selectivity and sensitivity of sensor array were used for comparing performance of sensor array as a result of two methods. The data acquired from selected sensor were analyzed by pattern analysis methods, principal component analysis and Sammon's mapping to analyze cluster tendency in the low space (2D). The sensor array by stepwise sensor elimination method had a better sensitivity and selectivity compared to a result of Wilks's lambda method.

• Bulletin of the Korean Chemical Society
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• v.31 no.11
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• pp.3084-3092
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• 2010

This paper describes the development of an automated, hand-held sensor for the fast assessment of seafood freshness. The sensor developed here combined: an array-based chemical sensor, composed of incrementally different conducting polymer elements deposited on a small chip; a highly sensitive, custom-made electronics for the detection of very small signal changes; precise temperature control of the sensor chamber; and an on-board microcontroller for data collection, storage, automation, and analysis. The instrument was used to successfully test seafood samples with different degree of freshness and spoilage. A linear relationship between microbiological count and e-Nose signal for three different fish fillet was developed. Once the linear relationship is included into the hand-held unit software, the e-Nose signal can be used for assessment of seafood freshness without performing the microbiological count technique.

• Journal of Sensor Science and Technology
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• v.22 no.2
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• pp.162-173
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• 2013

The purpose of this paper is to classify VOC gases by emulating the characteristics found in biological olfaction. For this purpose, we propose new signal processing method based a polymeric chemical sensor array consisting of 4096 sensors which is created by NEUROCHEM project. To remove unstable sensors generated in the manufacturing process of very large scaled chemical sensor array, we used discrete wavelet transformation and cosine similarity. And, to remove the supernumerary redundancy, we proposed the method of selecting candidates of representative sensor representing sensors with similar features by Fuzzy c-means algorithm. In addition, we proposed an improved algorithm for selecting representative sensors among candidates of representative sensors to better enhance classification ability. However, Classification for very large scaled sensor array has a great deal of time in process of learning because many sensors are used for learning though a redundancy is removed. Throughout experimental trials for classification, we confirmed the proposed method have an outstanding classification ability, at transient state as well as steady state.

• Journal of Sensor Science and Technology
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• v.23 no.5
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• pp.299-304
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• 2014

Optimizing the performance of a composite sensor array is necessary when the number of sensors to choose from is large. In this paper, we present a chemical sensors array optimization method using Wilks Lamda algorithm applicable a device to detect low concentration of alcohol from driver's exhale breath for interlocking engine ignition preventing drink-driving. More than 20 chemical sensors fabricated different synthetic stuffs and heater temperatures by collaborators were nominated, 5 sensors were selected for optimal sensors array using the method, and alcohol samples were well discriminated from the interference gases inside the vehicle. It has been confirmed by Principal Component Analysis (PCA).

• Journal of Sensor Science and Technology
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• v.25 no.3
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• pp.161-172
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• 2016

The use of a chemical sensor array can help discriminate between chemicals when comparing one sample with another. The ability to classify pattern characteristics from relatively small pieces of information has led to growing interest in methods of sensor recognition. A variety of pattern recognition algorithms, including the adaptive radial basis function network (RBFN), may be applicable to gas and/ or odor classification. In this paper, we provide a broad review of approaches for various types of gas and/or odor identification techniques based on RBFN and drift compensation techniques caused by sensor poisoning and aging.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.1231-1235
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• 2004

The needs of micro scale thermal detecting technique are increasing in biology and chemical industry. For example, Thermal finger print, Micro PCR(polymer chain reaction), ${\mu}TAS$ and so on. To satisfy these needs, we developed a DTSA(Diode Temperature Sensor Array) for detecting and controlling the temperature on small surface. The DTSA is fabricated by using VLSI technique. It consists of 32 ${\times}$ 32 array of diodes (1,024 diodes) for temperature detection and 8 heaters for temperature control on a 8mm ${\times}$ 8mm surface area. The working principle of temperature detection is that the forward voltage drop across a silicon diode is approximately proportional to the inverse of the absolute temperature of diode. And eight heaters ($1K{\Omega}$) made of poly-silicon are added onto a silicon wafer and controlled individually to maintain a uniform temperature distribution across the DTSA. Flip chip packaging used for easy connection of the DTSA. The circuitry for scanning and controlling DTSA are also developed

• Analytical Science and Technology
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• v.17 no.3
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• pp.217-224
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• 2004

A taste sensor system composed of mini electrode array was built in a flow cell. Potentiometric signals from 9 electrodes were collected for drinking waters and alcoholic beverages which were diluted in a low concentration buffer solution (0.005 M Tris-$H_2SO_4$ pH 7.2) for the measurement. The measured results were treated with the principal component analysis (PCA), and grouped on a two or three dimensional PCA coordinate to discriminate the tastes of each beverage. It is demonstrated that the taste sensor system of this work may be used for the quality control of beverages in production or the examination of their taste variation in the market.

• ETRI Journal
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• v.40 no.6
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• pp.802-812
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• 2018

Disease discrimination using an electronic nose is achieved by measuring the presence of a specific gas contained in the exhaled breath of patients. Many studies have reported the presence of acetone in the breath of diabetic patients. These studies suggest that acetone can be used as a biomarker of diabetes, enabling diagnoses to be made by measuring acetone levels in exhaled breath. In this study, we perform a chemical sensor array optimization to improve the performance of an electronic nose system using Wilks' lambda, sensor selection based on a principal component (B4), and a stepwise elimination (SE) technique to detect the presence of acetone gas in human breath. By applying five different temperatures to four sensors fabricated from different synthetic materials, a total of 20 sensing combinations are created, and three sensing combinations are selected for the sensor array using optimization techniques. The measurements and analyses of the exhaled breath using the electronic nose system together with the optimized sensor array show that diabetic patients and control groups can be easily differentiated. The results are confirmed using principal component analysis (PCA).

• Journal of Sensor Science and Technology
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• v.25 no.1
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• pp.13-19
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• 2016

Nowadays, most major automobile manufacturers are very interested, and actively involved, in developing driver alcohol detection system for safety (DADSS) that serves to prevent driving under the influence. DADSS measures the blood alcohol concentration (BAC) from the driver's breath and limits the ignition of the engine of the vehicle if the BAC exceeds the reference value. In this study, to optimize the sensor array of the DADSS, we selected sensors by using three different methods, configured the sensor arrays, and then compared their performance. The Wilks' lambda, stepwise elimination and filter method (using a principal component) were used as the sensor selection methods [2,3]. We compared the performance of the arrays, by using the selectivity and sensitivity as criteria, and Sammon mapping for the analysis of the cluster type of each gas. The sensor array configured by using the stepwise elimination method exhibited the highest sensitivity and selectivity and yielded the best visual result after Sammon mapping.