• Journal of Korea Society of Industrial Information Systems
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• v.19 no.3
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• pp.41-48
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• 2014

This paper proposes a new sensor circuit using a 32 nm carbon nanotube FET (CNFET) technology for artificial skin. For future robotic and prosthetic applications, it is essential to develop a robust and low power artificial skin for detecting the environment through touch. Therefore, a sensor circuit for the artificial skin also has to be developed to detect the sensor signals and convert them into digital bits. The artificial skin sensor is based on a mesh of sensors consisting of a nxn matrix using CNFET, and the sensor outputs are connected to a current monitoring circuit proposed as the sensor circuit. The proposed sensor provides pressure measurements and shape information about pressure distribution.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1314-1317
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• 1997

For realizing artificial skin sensing as a final goal, a mono-material pressure-conductive rubber sensor which is also sensitive for temperature is described. Firstly, discimination of the hardness and the thermal property of material using a proposed sensor is presented. Furthermore, a tactile sensor constints of four pressure-conductive rubber sensor to discriminate surface model which imitaties the surface roughness of material is proposed.

• Elastomers and Composites
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• v.56 no.3
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• pp.117-123
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• 2021

Electronic skin (or E-skin) is an artificial smart skin composed of one or more than two sensors. E-skins detect external stimuli and convert them into electrical signals. Various types of E-skin sensors exist, including mechanical, physical, and chemical, depending on the detection signals involved. For wearable E-skins with superior sensitivity and reliability, developing conductors that possess both good elasticity and sensitivity is essential. Typical electrical conductors used in these sensors show very high sensitivity, but they have drawbacks such as non-linearity, irreversibility, and a narrow sensing range. To address these issues, stretchable and lightweight ionic conductors have been actively used in E-skin applications. This study summarizes the recent progress on various types of ionic conductors and ionic-conductor-based E-skin sensors.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.11
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• pp.29-34
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• 2009

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.4
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• pp.897-902
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• 2018

The purpose of this study is to develop a bioinformatic diagnostic system that diagnoses the patient 's health condition by using the output waveform generated by applying the impulse voltage of 13Hz to 7 body parts based on DFM (Diagnose Fure Funktionelle Medizine) theory. It is expected that the data acquired by the diagnostic system will be served as a device for diagnosing the status of the body organ as well as the mesenchymal tissue through inductive reasoning based on artificial intelligence. In this paper, we will limit the system to acquire and manage bio-signals.

• Composites Research
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• v.35 no.6
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• pp.378-393
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• 2022

As an emerging power generation technology, triboelectric nanogenerators (TENGs) have received increasing attention due to their boundless promise in energy harvesting and self-powered sensing applications. The recent rise of soft robotics has sparked widespread enthusiasm for developing flexible and soft sensors and actuators. TENGs have been regarded as promising power sources for driving actuators and self-powered sensors, providing a unique approach for the development of soft robots with soft sensors and actuators. In this review, TENG-based soft robots with different morphologies and different functions are introduced. Among them, the design of biomimetic soft robots that imitate the structure, surface morphology, material properties, and sensing/generating mechanisms of nature has greatly benefited in improving the performance of TENGs. In addition, various bionic soft robots have been well improved compared to previous driving methods due to the simple structure, self-powering characteristics, and tunable output of TENGs. Furthermore, we provide a comprehensive review of various studies within specific areas of TENG-enabled soft robotics applications. We first explore various recently developed TENG-based soft robots and a comparative analysis of various device structures, surface morphologies, and nature-inspired materials, and the resulting improvements in TENG performance. Various ubiquitous sensing principles and generation mechanisms used in nature and their analogous artificial TENG designs are demonstrated. Finally, biomimetic applications of TENG enabled in tactile displays as well as in wearable devices, artificial electronic skin and other devices are discussed. System designs, challenges and prospects of TENGs-based sensing and actuation devices in the practical application of soft robotics are analyzed.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.8
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• pp.683-688
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• 2014

This paper presents a high-performance flexible tactile sensor based on inorganic silicon flexible electronics. We created 100 nm-thick semiconducting silicon ribbons equally distributed with 1 mm spacing and $8{\times}8$ arrays to sense the pressure distribution with high-sensitivity and repeatability. The organic silicon rubber substrate was used as a spring material to achieve both of mechanical flexibility and robustness. A thin copper layer was deposited and patterned on top of the pressure sensing layer to create a flexible temperature sensing layer. The fabricated tactile sensor was tested through a series of experiments. The results showed that the tactile sensor is capable of measuring pressure and temperature simultaneously and independently with high precision.

• Journal of Biomedical Engineering Research
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• v.11 no.2
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• pp.305-314
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• 1990

In this paper we have implemented and tested TPN which is system to supply sufficent nutrition to nutritionally deficient patient by means of ES (expert system) a kind of A.1 (artificial intelligence) . This system affords to evaluation of nutritional state of patient which is essential to physi- cian. who performs TPN, decision of performing TPN and management of patient-data & calculation of information needing to making TPN fluid. The features were as follolv 1. we input data, take ideal weight of patient and 24hr's creatlnln In urine according to chart in system compare TSF (triceps skin fold), MAC (mid-arm circumference), AMC (arm muscle circumference) to 5th, 15th, 50th percentile and evaluate the nutritional state of patient. 2. Calculation of protein & nonprotein calorie needing to treament of patient can be made exactly by stress factor, activity factor and body temperature. 3. patient's personal recording needing to management of patient date name of chief doc- tor, name of department of admission, chart number, history can by taken very easily. 4. The way of system operating is pull-down Menu one, It can be processing very efficiently. 5. Date processing in system, we can manage memory volume of computer verlr efficiently using of dynamic allocation variables. 6. We can make it very easy to edit & revise the input data, processed data is saved to diskette in 2 files (TDF, THF) , these are semipermanent preservation.

• Proceedings of the Korean Vacuum Society Conference
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• 2011.02a
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• pp.491-491
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• 2011

Transparent and flexible electronic devices that are light-weight, unbreakable, low power consumption, optically transparent, and mechanical flexible possibly have great potential in new applications of digital gadgets. Potential applications include transparent displays, heads-up display, sensor, and artificial skin. Recent reports on transparent and flexible field-effect transistors (tf-FETs) have focused on improving mechanical properties, optical transmittance, and performances. Most of tf-FET devices were fabricated with transparent oxide semiconductors which mechanical flexibility is limited. And, there have been no reports of transparent and flexible all-organic tf-FETs fabricated with organic semiconductor channel, gate dielectric, gate electrode, source/drain electrode, and encapsulation for sensor applications. We present the first demonstration of transparent, flexible all-organic sensor based on multifunctional organic FETs with organic semiconductor channel, gate dielectric, and electrodes having a capability of sensing infrared (IR) radiation and mechanical strain. The key component of our device design is to integrate the poly(vinylidene fluoride-triflouroethylene) (P(VDF-TrFE) co-polymer directly into transparent and flexible OFETs as a multi-functional dielectric layer, which has both piezoelectric and pyroelectric properties. The P(VDF-TrFE) co-polumer gate dielectric has a high sensitivity to the wavelength regime over 800 nm. In particular, wavelength variations of P(VDF-TrFE) molecules coincide with wavelength range of IR radiation from human body (7000 nm ~14000 nm) so that the devices are highly sensitive with IR radiation of human body. Devices were examined by measuring IR light response at different powers. After that, we continued to measure IR response under various bending radius. AC (alternating current) gate biasing method was used to separate the response of direct pyroelectric gate dielectric and other electrical parameters such as mobility, capacitance, and contact resistance. Experiment results demonstrate that the tf-OTFT with high sensitivity to IR radiation can be applied for IR sensors.

• Management & Information Systems Review
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• v.36 no.4
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• pp.33-51
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• 2017

With the advent of 'The Forth Industrial Revolution' and the growing demand for quality of life due to economic growth, needs for the quality of medical services are increasing. Artificial intelligence has been introduced in the medical field, but it is rarely used in chronic skin diseases that directly affect the quality of life. Also, atopic dermatitis, a representative disease among chronic skin diseases, has a disadvantage in that it is difficult to make an objective diagnosis of the severity of lesions. The aim of this study is to establish an intelligent severity recognition model of atopic dermatitis for improving the quality of patient's life. For this, the following steps were performed. First, image data of patients with atopic dermatitis were collected from the Catholic University of Korea Seoul Saint Mary's Hospital. Refinement and labeling were performed on the collected image data to obtain training and verification data that suitable for the objective intelligent atopic dermatitis severity recognition model. Second, learning and verification of various CNN algorithms are performed to select an image recognition algorithm that suitable for the objective intelligent atopic dermatitis severity recognition model. Experimental results showed that 'ResNet V1 101' and 'ResNet V2 50' were measured the highest performance with Erythema and Excoriation over 90% accuracy, and 'VGG-NET' was measured 89% accuracy lower than the two lesions due to lack of training data. The proposed methodology demonstrates that the image recognition algorithm has high performance not only in the field of object recognition but also in the medical field requiring expert knowledge. In addition, this study is expected to be highly applicable in the field of atopic dermatitis due to it uses image data of actual atopic dermatitis patients.