• The Journal of Korea Robotics Society
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• v.13 no.4
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• pp.265-271
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• 2018

The recent prosthetic technologies pursue to control multi-DOFs (degrees-of-freedom) hand and wrist. However, challenges such as high cost, wear-ability, and motion intent recognition for feedback control still remain for the use in daily living activities. The paper proposes a multi-channel knit band sensor to worn easily for surface EMG-based prosthetic control. The knitted electrodes were fabricated with conductive yarn, and the band except the electrodes are knitted using non-conductive yarn which has moisture wicking property. Two types of the knit bands are fabricated such as sixteen-electrodes for eight-channels and thirty-two electrodes for sixteen-channels. In order to substantiate the performance of the biopotential signal acquisition, several experiments are conducted. Signal to noise ratio (SNR) value of the knit band sensor was 18.48 dB. According to various forearm motions including hand and wrist, sixteen-channels EMG signals could be clearly distinguishable. In addition, the pattern recognition performance to control myoelectric prosthesis was verified in that overall classification accuracy of the RMS (root mean squares) filtered EMG signals (97.84%) was higher than that of the raw EMG signals (87.06%).

• Textile Coloration and Finishing
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• v.35 no.3
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• pp.179-187
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• 2023

In this study, we developed a microfiber-based flexible pressure sensor with high sensitivity and excellent skin breathability. A nonwoven fabric composed of microfibers was prepared by electrospinning, which resulted in excellent moisture permeability of the sensor (143 g∙m^-2∙h^-1). In particular, high-pressure sensitivity (0.36 kPa^-1) was achieved by introducing submicron structures on the microfiber surface by controlling the ambient humidity during electrospinning. The fabrication technology of the microfiber-based flexible pressure sensors reported in this study is expected to contribute to the commercialization of flexible pressure sensors applicable to long-term wearable health monitoring as well as virtual/augmented reality and electronic skin applications.

• Proceedings of the Korean Fiber Society Conference
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• 2003.10a
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• pp.25-26
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• 2003

Electrically conducting polymers such as polypyrrole(PPy) or poly(3,4-ethylene dioxythiophene)(PEDOT) were sequentially polymerized chemically and electrochemically on various kinds of woven fabrics, giving rise to the fabrics with high electrical conductivity. The specific volume resistivity of the fabric prepared in this study was extremely low as 0.2 $\Omega$-cm. We figured out the electrically conducting fabrics were practically useful for many applications such as an EMI shielding material, a flexible surface heating element or a strain sensor for large deformation.

• Proceedings of the Korean Society of Computer Information Conference
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• 2012.07a
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• pp.411-412
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• 2012

본 논문에서는 인간의 가장 기본적이며 기초적인 운동인 걸음걸이로부터 검출할 수 있는 걸음 수 및 보행분석을 위해 전도성 섬유를 이용한 전기용량성압력 센서를 깔창형태로 개발하였다. 개발된 깔창 형태의 센서는 보행시의 압력을 측정하여 보행신호를 검출하고, 검출된 신호를 이용하여 걸음 수 및 보행 분석을 실시하였다. 개발된 센서의 성능 검증을 위하여 상용 만보계 및 관찰자의 수계로 도출된 보수를 비교하였으며, 자세에 따른 압력차이를 측정하였다. 기존의 상용 만보계는 저속(1 Km/h)으로 걸었을 때 보수가 잘 측정되지 않은 반면 개발된 센서는 저속에서도 관찰자 수계대비 정확한 보수를 도출 할 수 있었다. 또한 자세에 따라 압력 값을 토대로 사용자의 자세를 모니터링 할 수 있음을 보였다. 본 연구는 향후 스마트폰과 무선 연동하는 스마트 보행관리 시스템을 개발하기 위한 기초연구이다.

• Journal of Electrical Engineering and Technology
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• v.10 no.1
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• pp.364-371
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• 2015

In this study, we developed a feasible structure of a textile-based inductive sensor using a machine embroidery method, and applied it to a non-contact type vital sign sensing device based on the principle of magnetic-induced conductivity. The mechanical heart activity signals acquired through the inductive sensor embroidered with conductive textile on fabric were compared with the Lead II ECG signals and with respiration signals, which were simultaneously measured in every case with five subjects. The analysis result showed that the locations of the R-peak in the ECG signal were highly associated with sharp peaks in the signals obtained through the textile-based inductive sensor (r=0.9681). Based on the results, we determined the feasibility of the developed textile-based inductive sensor as a measurement device for the heart rate and respiration characteristics.

• Korean Chemical Engineering Research
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• v.59 no.2
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• pp.159-164
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• 2021

As the attachable-type wearable devices have received considerable interests, the need for the development of high-performance electrode materials of fabric or textiles type is emerging. In this study, we demonstrated the electrochemical property of CNT fibers electrode as a flexible electrode material and its non-enzymatic glucose sensing performance. Surface morphology of CNT fibers was observed by SEM. And the electrochemical characteristics were investigated by cyclic voltammetry, electrochemical impedance spectroscopy and chronoamperometry. The CNT fibers based sensor exhibited improved sensing performances such as high sensitivity, a wide linear range, and low detection limit due to improved electrochemical properties such as low capacitive current, good electrochemical activity by efficient direct electron transfer between the redox species and the electrode interface. Therefore, this study is expected to be used as a basic research for the development of high performance flexible electrode materials based on CNT fibers.

• The Journal of Korea Robotics Society
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• v.15 no.3
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• pp.240-247
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• 2020

This paper presents a novel knitted data glove system for pattern classification of hand posture. Several experiments were conducted to confirm the performance of the knitted data glove. To find better sensor materials, the knitted data glove was fabricated with stainless-steel yarn and silver-plated yarn as representative conductive yarns, respectively. The result showed that the signal of the knitted data glove made of silver-plated yarn was more stable than that of stainless-steel yarn according as the measurement distance becomes longer. Also, the pattern classification was conducted for the performance verification of the data glove knitted using the silver-plated yarn. The average classification reached at 100% except for the pointing finger posture, and the overall classification accuracy of the knitted data glove was 98.3%. With these results, we expect that the knitted data glove is applied to various robot fields including the human-machine interface.

• Journal of Sensor Science and Technology
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• v.32 no.2
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• pp.88-94
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• 2023

Recently, piezoelectric tactile sensors have garnered considerable attention in the field of texture recognition owing to their high sensitivity and high-frequency detection capability. Despite their remarkable potential, improving their mechanical flexibility to attach to complex surfaces remains challenging. In this study, we present a flexible piezoelectric sensor that can be bent to an extremely small radius of up to 2.5 mm and still maintain good electrical performance. The proposed sensor was fabricated by controlling the thickness that induces internal stress under external deformation. The fabricated piezoelectric sensor exhibited a high sensitivity of 9.3 nA/kPa ranging from 0 to 10 kPa and a wide frequency range of up to 1 kHz. To demonstrate real-time texture recognition by rubbing the surface of an object with our sensor, nine sets of fabric plates were prepared to reflect their material properties and surface roughness. To extract features of the objects from the detected sensing data, we converted the analog dataset to short-term Fourier transform images. Subsequently, texture recognition was performed using a convolutional neural network with a classification accuracy of 97%.

• Science of Emotion and Sensibility
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• v.26 no.4
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• pp.41-50
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• 2023

This study aims to develop electromyography (EMG) textile electrodes and assess their performance and signal stability by examining variations in layer count and fabric types. We fabricated the electrodes through layering and pressing techniques, focusing on configurations with different layer counts (Layer-0, Layer-1, and Layer-2). Our findings indicate that layer presence significantly influences muscle activation measurements, with enhanced performance correlated with increased layer numbers. Subsequently, we created electrodes from five distinct fabrics (neoprene, spandex cushion, 100% polyester, nylon spandex, and cotton canvas), each maintaining a Layer-2 structure. In performance tests, nylon spandex fabric, particularly heavier variants, outperformed others, while the spandex cushion electrodes showed superior stability in muscle activation signal acquisition. This research elucidates the connection between electrode performance and factors like layer number and electrode-skin contact area. It suggests a novel approach to electrode design, focusing on layer properties and targeted pressure application on specific sensor areas, rather than uniformly increasing sleeve pressure.

• Science of Emotion and Sensibility
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• v.21 no.1
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• pp.35-44
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• 2018

This study suggests the sensing method of the Three-dimensional respiration rate sensor based on surface area changes, and exploring the design direction of the three-dimensional breathing sensor and the design orientation of the garment. To achieve this, two types of three-dimensional respiration rate sensor were produced, and the study of the dummy and the subjects studied. The study I investigated the possibility of measurement of the three-dimensional respiration sensor by the study variables of the sensor type and speed of respiration. The study II proposes a suitable type of sensor for each of the three measuring positions in addition to the study variables in the study I. To evaluate accuracy, reproducibility, and reliability of the three-dimensional respiration rate sensor, the BIOPAC was used to measure the respiration rate simultaneously with the three-dimensional respiration rate sensor. Through all these results of the experiment, it explored the possibility of measurement of the three-dimensional respiration sensor for the dummy. It also proposed a suitable type of sensor by measuring the respiration rate for the human body.