• Journal of IKEEE
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• v.22 no.1
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• pp.174-179
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• 2018

In this paper, design of high-efficiency DC-DC converter is presented for low-power PMIC (power management integrated circuit). As PMIC technologies for IoT and wearable devices have been continuously improved, high-efficiency energy harvesting schemes should be essential. Since the supply voltage resulting from energy harvesting is low and widely variable, design techniques to achieve high efficiency over a wide input voltage range are required. To obtain a constant switching frequency for wide input voltage range, frequency compensation circuit using supply-voltage variation sensing circuit is included. In order to obtain high efficiency performance at very low-power condition, accurate burst-mode control circuit was adopted to control switching operations. In the proposed DC-DC buck converter, output voltage is set to be 0.9V at the input voltage of 0.95~3.3V and maximum measured efficiency is up to 78% for the load current of 180uA.

• Journal of Sensor Science and Technology
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• v.27 no.3
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• pp.186-191
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• 2018

Smart textile industries have been precipitously developed and extended to electronic textiles and wearable devices in recent years. In particular, owing to an increasingly aging society, the elderly healthcare field has been highlighted in the smart device industries, and pressure sensors can be utilized in various elderly healthcare products such as flooring, mattress, and vital-sign measuring devices. Furthermore, elderly healthcare products need to be more lightweight and flexible. To fulfill those needs, textile-based pressure sensors is considered to be an attractive solution. In this research, to apply a textile to the second layer using a pressure sensing device, a novel type of conductive textile was fabricated using vapor phase polymerization of poly(3,4-ethylenedioxythiophene) (PEDOT). Vapor phase polymerization is suitable for preparing the conductive textile because the reaction can be controlled simply under various conditions and does not need high-temperature processing. The morphology of the obtained PEDOT-conductive textile was observed through the Field Emission Scanning Electron Microscope (FESEM). Moreover, the resistance was measured using an ohmmeter and was confirmed to be adjustable to various resistance ranges depending on the concentration of the oxidant solution and polymerization conditions. A 3-layer 81-point multi-pressure sensor was fabricated using the PEDOT-conductive textile prepared herein. A 3D-viewer program was developed to evaluate the sensitivity and multi-pressure recognition of the textile-based multi-pressure sensor. Finally, we confirmed the possibility that PEDOT-conductive textiles could be utilized by pressure sensors.

• The KIPS Transactions:PartA
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• v.17A no.3
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• pp.145-152
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• 2010

Most wearable system for mobile healthcare applications consists of three parts. The first part is the sensing elements based on bio-signal, the second is the circuit module for control, data acquisition and wireless communication and control and the third is garment with a built-in electrodes and circuits. The existing healthcare garment systems have to find a solution to signal-wire and uncomfortable and inappropriate electrode to long-term attachment. Even if the wireless communication is used for healthcare garment system, the interface between sensors and circuits have to use wires. To solve these problems, this paper use electrode using PEDOT coated PVDF nanoweb for ECG signal and PVDF film sensor for respiratory signal. And, we constructed garment network using digital yarn of 10um, and transmitted ECG and respiratory signal to mobile phone through the integrated circuit with bluetooth called station To evaluate feasibility of the proposed mobile healthcare garment system, we experimented with transmission and measurement of ECG and respiratory signal using nanoweb electrode and digital yarn. We got a successful result without noise and attenuation.

• Journal of Digital Contents Society
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• v.19 no.9
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• pp.1779-1785
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• 2018

In this paper, we propose an error correction method to improve the accuracy of human activity recognition using sensor event data obtained by smart devices such as wearable and smartphone. In the context awareness through the smart device, errors inevitably occur in sensing the necessary context information due to the characteristics of the device, which degrades the prediction performance. In order to solve this problem, we apply Kalman filter's error correction algorithm to compensate the signal values obtained from 3-axis acceleration sensor of smart device. As a result, it was possible to effectively eliminate the error generated in the process of the data which is detected and reported by the 3-axis acceleration sensor constituting the time series data through the Kalman filter. It is expected that this research will improve the performance of the real-time context-aware system to be developed in the future.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.476-496
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• 2018

With the advancement and deployment of wireless communication techniques, wireless body area network (WBAN) has emerged as a promising approach for e-healthcare that collects the data of vital body parameters and movements for sensing and communicating wearable or implantable healthful related information. In order to avoid any possible rancorous attacks and resource abuse, employing lightweight ciphers is most effective to implement encryption, decryption, message authentication and digital signature for security of WBAN. As a typical lightweight cryptosystem with an extended sponge function framework, the PHOTON family is flexible to provide security for the RFID and other highly-constrained devices. In this paper, we propose a differential fault analysis to break three flavors of the PHOTON family successfully. The mathematical analysis and simulating experimental results show that 33, 69 and 86 random faults in average are required to recover each message input for PHOTON-80/20/16, PHOTON-160/36/36 and PHOTON-224/32/32, respectively. It is the first result of breaking PHOTON with the differential fault analysis. It provides a new reference for the security analysis of the same structure of the lightweight hash functions in the WBAN.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.1
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• pp.63-71
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• 2020

Recently, to improve convenience, flexible electronics are quickly being developed for a number of application areas. Flexible electronic devices comprise characters such as being bendable, stretchable, foldable, and wearable. Effectively manufacturing flexible electronic devices requires high efficiency, low costs, and simple processes for manufacturing technology. Through this study, we enabled the rapid production of multifunctional flexible bending sensors using a simple, low-cost Fused Deposition Modeling (FDM) 3D printer. Furthermore, we demonstrated the possibility of the rapid production of a range of functional flexible bending sensors using a simple, low-cost FDM 3D printer. Accurate and reproducible functional materials made by FDM 3D printers are an effective tool for the fabrication of flexible sensor electronic devices. The 3D-printed flexible bending sensor consisted of polyurethane and a conductive filament. Two patterns of electrodes (straight and Hilbert curve) for the 3D printing flexible sensor were fabricated and analyzed for the characteristics of bending displacement. The experimental results showed that the straight curve electrode sensor sensing ability was superior to the Hilbert curve electrode sensor, and the electrical conductivity of the Hilbert curve electrode sensor is better than the straight curve electrode sensor. The results of this study will be very useful for the fabrication of various 3D-printed flexible sensor devices with multiple degrees of freedom that are not limited by size and shape.

• Journal of Biomedical Engineering Research
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• v.30 no.6
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• pp.503-509
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• 2009

The development of technology has led to ubiquitous health care service, which enables many patients to receive medical services anytime and anywhere. For the ubiquitous health care environment, real-time measurement of biomedical signals is very important, and the medical instruments must be small and portable or wearable. So, such devices have been developed to measure biomedical signals. In this study, we develop the biomedical monitoring device which is sensing the PPG signal, one of the useful signal in the field of ubiquitous healthcare. We design a watch-like biomedical signal monitoring system without a finger probe to prevent the user's inconvenience. This system obtains the PPG from the radial artery using a sensor in the wrist band. But, new device developed in this paper is easy to get the motion artifacts. So, we proposed new algorithm removing the motion artifacts from the PPG signal. The method detects motion artifacts by changing the degree of brightness of the light source. If the brightness of the light source is reduced, the PPG pulses will disappear. When the PPG pulses have disappeared completely, the remaining signal is not the signal that results from the changing blood flow. We believe that this signal is the motion artifact and call it the noise reference signal. The motion artifacts are removed by subtracting the noise reference signal from the input signal. We apply this algorithm to the system, so we can stabilize the biomedical monitoring system we designed.

• Advances in Computational Design
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• v.4 no.2
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• pp.73-90
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• 2019

The growth in the number of single-member households is a critical issue worldwide, especially among the elderly. For those living alone, who may be unaware of their health status or routines that could improve their health, a continuous healthcare monitoring system could provide valuable feedback. Assessing the performance adequacy of activities of daily living (ADL) can serve as a measure of an individual's health status; previous research has focused on determining a person's daily activities and extracting the most frequently performed behavioral patterns using camera recordings or wearable sensing techniques. However, existing methods used to extract common patterns of an occupant's activities in the home fail to address the spatio-temporal dimensions of human activities simultaneously. Though multiple sequence alignment (MSA) offers some advantages - such as inherent containment of the spatio-temporal data in sequence format, and rapid identification of hidden patterns - MSA has rarely been used to extract in-home ADL routines. This research proposes a method to extract a household occupant's ADL routines from a cumulative spatio-temporal data log of occupancy collected using a non-intrusive method (i.e., a tomographic motion detection system). The findings from an occupant's 28-day spatio-temporal activity log demonstrate the capacity of the proposed approach to identify routine patterns of an occupant's daily activities and to reveal the order, duration, and frequency of routine activities. Routine ADL patterns identified from the proposed approach are expected to provide a basis for detecting/evaluating abrupt or gradual changes of an occupant's ADL patterns that result from a physical or mental disorder, and can offer valuable information for home automation applications by enabling the prediction of ADL patterns.

• Korean Chemical Engineering Research
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• v.57 no.5
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• pp.606-610
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• 2019

In this study, we demonstrated that the nonenzymatic glucose sensor based on the flexible carbon fiber bundle electrode with BDD nanocomposites (CF-BDD electrode). As a nano seeding method for the deposition of BDD on flexible carbon fiber, electrostatic self-assembly technique was employed. Surface morphology of BDD coated carbon fiber electrode was observed by scanning electron microscopy. And the electrochemical characteristics were investigated by cyclic voltammetry, electrochemical impedance spectroscopy and chronoamperometry. This CF-BDD electrode exhibited a large surface area, a direct electron transfer between the redox species and the electrode surface and a high catalytic activity, resulting in a wider linear range (3.75~50 mM), a faster response time (within 3 s) and a higher sensitivity (388.8 nA/mM) in comparison to a bare CF electrode. As a durable and flexible electrochemical sensing electrode, this brand new CF-BDD scheme has promising advantages on various electrochemical and wearable sensor applications.

• Applied Chemistry for Engineering
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• v.34 no.4
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• pp.347-356
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• 2023

Liquid crystal elastomer (LCE) fibers have been widely applied in various fields, such as soft robots and biomimetic actuators, in a one-dimensional form. LCEs possess the characteristics of both fluidity and solid order, as well as the elasticity of rubber, and exhibit stimulus-response based on these properties. In particular, by programming the responsiveness to various stimuli such as heat, light, electric fields, and magnetic fields in terms of shape-changing, various movements such as lifting, twisting, and rotating can be realized with high degrees of freedom. Therefore, LCE fibers have the potential for application in various fields such as artificial muscles, soft robots, wearable technologies, and sensing technologies. The research on liquid crystal elastomer fibers is evaluated to have high applicability in various fields in the Fourth Industrial Revolution as a smart material that can include various functionalities beyond simple fibers. In this review, we introduce the structure and basic characteristics of liquid crystal elastomer fibers, the latest research trends on orientation-based fabrication methods, and various applications such as artificial muscles, smart fabrics, and soft robots.