• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.602-604
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• 2004

A portable electronic tongue(E-Tongue) system using an array of ion-selective electrode(ISE) and personal digital assistants(PDA) for recognizing and analyzing food and drink have been designed. By the employment of PDA, the complex algorithm such as fuzzy c-means algorithm(FCMA) could be used in E-Tongue, FCMA could iteratively solve the cluster centers of pre-determined standard patterns. And the membership between the standard patterns and unknown pattern could be analyzed easily by the present E-Tongue combined with PDA.

• Journal of Sensor Science and Technology
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• v.13 no.6
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• pp.446-453
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• 2004

A portable electronic tongue (E-Tongue) system using an array of ion-selective electrode (ISE) and personal digital assistants (PDA) for recognizing and analyzing food and drink have been designed. By the employment of PDA, the complex algorithm such as fuzzy c-means algorithm (FCMA) could be used in E-Tongue, PUMA could iteratively solve the cluster centers of pre-determined standard patterns. And the membership between the standard patterns and unknown pattern could be analyzed easily by the present E-Tongue combined with PDA.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.2
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• pp.109-116
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• 2005

In this paper, we investigate the visual and quantitative analysis at the same time with an electronic tongue(e-tongue) system using an array of ISE(ion-selective electrode). We apply the FCM(fuzzy c-means) algorithm combined with PCA(principal component analysis), which can be reduced multi-dimensional data to third-dimensional data, to classify data patterns detected by E-Tongue system. The proposed technique can be designed to solve the cluster centers and membership grade of patterns combined with the output results obtained by PCA method. According to the proposed technique, the membership grade of unknown pattern, which does not shown previously can be determined and analyzed visually. Conclusionally, the relationship between the standard patterns and unknown pattern can be easily analyzed. Throughout the experimental trials, the proposed technique has been confirmed using developed E-Tongue system.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.921-926
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• 2022

Sugar solutions (5%, 10%, 15% and 20%) were tested by seven sensors of Astree E-Tongue for selecting a sensor for sweetness. NMS sensor was chosen as a sensor for sweetness among two sensors (PKS and NMS sensors selected in first stage) by considering precision, linearity and accuracy. Sugar, fructose, glucose and xylitol (5%, 10% and 15%) were tested by E-tongue. The principal component analysis (PCA) result by E-Tongue with seven sensors at 5% concentration level of four sweetners was not satisfactory (Discrimination index was -0.1). On the other hand, the relative NMS sensor response values were derived as 1.08 (fructose), 0.99 (glucose) and 1.00 (xylitol) comparing to sugar. Only the E-Tongue relative glucose response 0.99 was different from 0.5~0.75 of the relative sweetness range reported as the human sensory test results. Considering the excellent precision (%RSD, 1.53~3.64%) of E-Tongue using NMS single sensor for three types of sweeteners compared to sugar in the concentration range of 5% to 15%, replacing sensory test of sweetened beverages by E-Tongue might be possible for new product development and quality control.

• Journal of the Korean Society of Tobacco Science
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• v.27 no.1 s.53
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• pp.134-140
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• 2005

The purpose of this study was the discrimination of different tobacco types by the E-Nose/tongue and the analysis of what human sensory attributes are correlated with e-instrument's sensors. Samples were made from five groups of Korean domestic tobacco leaves, aged burley and not aged, aged flue-cured and not aged and blending types of the four. Instrumental tests were conducted to discriminate characteristics among different tobacco samples by the E-Nose and the E-Tongue. Sensory attributes of tobacco tastes were impact, irritation, bitterness, hay-like, tobacco taste, smoke volume, smoke pungent and mouth cleanness. STATISTICA software was used to analyze correlation between the human sensory data and the raw data of e-instruments. Discrimination analysis can be achieved using principal components analysis (PCA) and discriminant factorial analysis(DFA). As a result, impact, bitterness, irritation, smoke volume and smoke pungent of human sensory attributes were correlated with data from the several clustered E-Nose sensors(p < 0.10). And bitterness, irritation, and smoke pungent of human sensory attributes were correlated with data from the E-Tongue sensors(p < 0.10). PCA plot by the E-Nose shows that aged tobacco and not aged were discriminated and DFA plot shows that three groups(aged burley, not aged burley and flue-cured) were discriminated. PCA plot by the E- Tongue shows that flue-cured tobacco was separated from burley. Our results indicated that the e-instruments are sensitive enough to distinguish among tobacco types and their several sensors are reacted to the human sensory attributes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.945-961
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• 2019

Tongue diagnosis is one of the most important diagnostic methods in Traditional Chinese Medicine (TCM). Tongue image segmentation aims to extract the image object (i.e., tongue body), which plays a key role in the process of manufacturing an automated tongue diagnosis system. It is still challenging, because there exists the personal diversity in tongue appearances such as size, shape, and color. This paper proposes an innovative segmentation method that uses image thresholding, gray projection and active contour model (ACM). Specifically, an initial object region is first extracted by performing image thresholding in HSI (i.e., Hue Saturation Intensity) color space, and subsequent morphological operations. Then, a gray projection technique is used to determine the upper bound of the tongue body root for refining the initial object region. Finally, the contour of the refined object region is smoothed by ACM. Experimental results on a dataset composed of 100 color tongue images showed that the proposed method obtained more accurate segmentation results than other available state-of-the-art methods.

• Journal of Sensor Science and Technology
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• v.14 no.6
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• pp.444-454
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• 2005

The IEEE 1451.4 standards defines an architectural model for interfacing smart transducers for sensors & actuators. This standard allows analogue transducers to communicate their identification and calibration data in a digital format. A digital format is called the TEDS (transducer electronic data sheet). However, the standard template TEDS of IEEE 1451.4 do not supports sensors to use in electronic tongue system, such as arrayed-potentiometric and voltametric sensors. In this paper, a solution to standardize sensors for E-Tongue (electronic tongue) and electronic tongue systems is presented.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.133-137
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• 2005

In this paper, we investigate visual and quantitative analysis of different tastes in the liquids using multi-array chemical sensor (MACS) based on the ion-selective electrodes (ISEs), which is so called the electronic tongue (E-Tongue) system. We apply the Fuzzy C-means (FCM) algorithm combined with Principal Component Analysis (PCA), which can be used to reduce multi-dimensional data to two- or three-dimensional data, to classify visually data patterns detected by E-Tongue system. The proposed technique can be determined the cluster centers and membership grade of patterns through the unsupervised way. The membership grade of an unknown pattern, which does not shown previously, can be visually and analytically determined. Throughout the experimental trails, the E-tongue system combined with the proposed algorithms is demonstrated robust performance for visual and quantitative analysis for different tastes in the liquids.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.6 no.2
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• pp.149-158
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• 2005

In this paper, we have designed and implemented a portable e-tongue (electronic tongue) system using MACS (multi array chemical sensor) and PDA. The system embedded in PDA has merits such as comfortable user interface and data transfer by internet from on-site to remote computer. MACS was made up 7 electrodes (${NH_4}^+$, $Na^+$, $Cl^-$, ${NO_3}^-$, $K^+$, $Ca^{2+}$, $Na^+$, pH) and a reference electrode. For learning the system, we adapted the Levenberg-Marquardt algorithm based on the back-propagation, which could iteratively learned the pre-determined standard patterns, in e-tongue system. Conclusionally, the relationship between the standard patterns and unknown pattern can be easily analyzed. The e-tongue was applied to whiskeys and cognac (one high level whisky, one low level whiskey, two cognac) and 2 sample whiskeys for each standard patterns and unknown patterns. The relationship between the standard patterns and unknown patterns can be easily analyzed.

• The Korean Journal of Food And Nutrition
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• v.31 no.2
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• pp.264-271
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• 2018

The objective of this study was to investigate taste profiles and the correlation of Doenjang soup solution prepared with three different temperatures (5, 25, $45^{\circ}C$) and using an electronic nose (e-nose), electronic tongue (e-tongue), and descriptive analyses by trained panelists. A total of 17sensory attributes were generated from the descriptive analyses for the Doenjang soup solution. There were significant difference among the samples in the cooked soybean flavor, the cooked soybean odor, the soy sauce odor, the sweet odor, the sweet taste, and the sweet aftertaste attributes. The intensities of these sensory attributes tended to increase as the serving temperature of the Doenjang soup solution increased. There were seven volatile compounds detected by the electronic nose: ethanol, propanal, 2-methylpropanal, ethyl acetate, 3-methylbutanal, and beta-pinene. The intensities of the volatile compounds increased as the temperature of the Doenjang soup solution increased. On the other hand, the intensities of the basic tastes by the e-tongue decreased as the temperature of the Doenjang soup solution increased. In conclusion, the e-nose, e-tongue, and descriptive analysis results showed different correlations depending on the temperature of the Doenjang soup solutions.