• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.26 no.1
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• pp.16-23
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• 2015

In this paper, a bent microstrip patch antenna, which is suitable for band-type wearable devices and RF configuration, to be used in the WCDMA2100 mobile network is proposed. The proposed antenna using RF configuration which is consisted of separated Tx and Rx frequency band is designed to operate or function in WCDMA2100 Tx frequency band only and it is not strongly affected by the human body because of the conductor at the bottom side. At both flat case and bent case, the proposed antenna's maximum gain satisfies at least 5.3 dBi, and its -6 dB return loss bandwidth is wider than 20 MHz. The simulated surface absorption rate($SAR_{1g}$) result is under 0.7 [W/kg]. The proposed antenna suits in band-type wearable devices which is worn on wrists or arms.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.1
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• pp.153-162
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• 2018

The importance of energy harvesting technique is increasing due to the elevated level of demand for sustainable power sources for wearable device applications. In this study, we developed an Energy Harvesting wearable Platform(EH-P) architecture which is used in the design of a multi-energy source based on TENG. The proposed switching circuit produces power with higher current at lower voltage from energy harvesting sources with lower current at higher voltage. This can powers microcontrollers for a short period of time by using PV and TENG complementarily placed under hard conditions for the sources such as indoors. As a result, the whole interface circuit is completely self-powered with this makes it possible to run of sensing on a Wearable device platform. It was possible to increase the wearable device life time by supplying more than 29% of the power consumption to wearable devices. The results presented in this paper show the potential of multi-energy harvesting platform for use in wearable harvesting applications, provide a means of choosing the energy harvesting source.

• Journal of Biomedical Engineering Research
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• v.28 no.2
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• pp.280-286
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• 2007

The wearable sensor glove was developed using EDA sensors and conducting fabric. EDA(Electro-dermal Activity) signal is an electric response of human skin. There are SIL(Skin Impedance Level) and SIR(Skin Impedance Response) in EDA. SIL consists mostly of a DC component while SIR consists of an AC component. The relationship between drowsiness and the EDA signal is utilized. EDA sensors were made using a conducting fabric instead of AgCl electrodes, for a more suitable, more wearable device. The EDA signal acquisition module was made by connecting the EDA sensor gloves through conductive fabric lines. Also, the EDA signal acquisition module can be connected to a PC that shows the results of the EDA signal processing analysis and gives proper feedback to the user. This system can be used in various applications to detect drowsiness and prevent accidents from drowsiness for automobile drivers.

• Vacuum Magazine
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• v.3 no.3
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• pp.15-18
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• 2016

In future wearable electronic systems, 3-dimensional (3D) devices have attracted much attention due to their high density integration and low-power functionality. Among 3D devices, gate-all-around (GAA) nanowire transistor provides superior gate controllability, resulting in suppressing short channel effect and other drawbacks in 2D metal-oxide-semiconductor field-effect transistor (MOSFET). Silicon nanowires (SiNWs) are the most promising building block for GAA structure device due to their compatibility with the current Si-based ultra large scale integration (ULSI) technology. Moreover, the theoretical limit for subthreshold swing (SS) of MOSFET is 60 mV/dec at room temperature, which causes the increase in Ioff current. To overcome theoretical limit for the SS, it is crucial that research into new types of device concepts should be performed. In our present studies, we have experimentally demonstrated feedback FET (FBFET) and tunnel FET (TFET) with sub-60 mV/dec based on SiNWs. Also, we fabricated SiNW based complementary TFET (c-TFET) and SiNW complementary metal-oxide-semiconductor (CMOS) inverter. Our research demonstrates the promising potential of SiNW electronic devices for future wearable electronic systems.

• PNF and Movement
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• v.18 no.2
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• pp.287-296
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• 2020

Purpose: The study aims were to develop a wearable inertial sensor-based gait analysis device that uses machine learning algorithms, and to validate this novel device using temporal gait parameters. Methods: Thirty-four healthy young participants (22 male, 12 female, aged 25.76 years) with no musculoskeletal disorders were asked to walk at three different speeds. As they walked, data were simultaneously collected by a motion capture system and inertial measurement units (Reseed®). The data were sent to a machine learning algorithm adapted to the wearable inertial sensor-based gait analysis device. The validity of the newly developed instrument was assessed by comparing it to data from the motion capture system. Results: At normal speeds, intra-class correlation coefficients (ICC) for the temporal gait parameters were excellent (ICC [2, 1], 0.99~0.99), and coefficient of variation (CV) error values were insignificant for all gait parameters (0.31~1.08%). At slow speeds, ICCs for the temporal gait parameters were excellent (ICC [2, 1], 0.98~0.99), and CV error values were very small for all gait parameters (0.33~1.24%). At the fastest speeds, ICCs for temporal gait parameters were excellent (ICC [2, 1], 0.86~0.99) but less impressive than for the other speeds. CV error values were small for all gait parameters (0.17~5.58%). Conclusion: These results confirm that both the wearable inertial sensor-based gait analysis device and the machine learning algorithms have strong concurrent validity for temporal variables. On that basis, this novel wearable device is likely to prove useful for establishing temporal gait parameters while assessing gait.

• Physical Therapy Korea
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• v.28 no.4
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• pp.251-255
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• 2021

Background: Physical activity and quality of life (QOL) influence the health status of older adults. Recently, the use of wearable devices to monitor physical activity has increased. Objects: This study examined the relationship between the amount of physical activity, measured using a wearable device, and QOL among older adults. Methods: In total, 71 older adults (aged ≥ 65 years) were enrolled. The amount of physical activity was measured using a wearable device with a wrist strap, and daily physical activity was classified according to intensity (sedentary, light, moderate, or very active). Self-reported QOL was evaluated using the Short Form 36 (SF-36) questionnaire. Pearson and Spearman correlation analyses were conducted to analyze parametric and non-parametric variables, respectively. The relationship between amount of daily physical activity and SF-36 scores was assessed. Results: The correlation analyses revealed positive correlations between the amount of moderate-intensity and very active physical activity (minutes/day) and SF-36 scores (p < 0.05). Conclusion: Physical activity of at least moderate intensity is associated with better QOL in older adults. Further studies are required to verify the effects of increased physical activity on QOL in older adults.

• Journal of Welding and Joining
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• v.32 no.3
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• pp.34-42
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• 2014

Flexible devices have been developed from their rigid, heavy origins to become bendable, stretchable and portable. Such a paper displays, e-skin, textile electronics are emerging research areas and became a mainstream of overall industry. Thin film transistors, diodes and sensors built on plastic sheets, textile and other unconventional substrates have a potential applications in wearable displays, biomedical devices and electronic system. In this review, we describe current trends in technologies for flexible/wearable electronics.

• Journal of Fashion Business
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• v.18 no.4
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• pp.1-14
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• 2014

Currently smart textile market is rapidly expanding and the demand is increasing integration of an electronic fiber circuit. The garments are an attractive platform for wearable device. This is one of the integration techniques, which consists of is the selective introduction of conductive yarns into the fabric through knitting, weaving or embroidering. The aim of this work is to develop a golf bend driven prototype design for an attachable Arduino that can be used to assess elbow motion. The process begins with the development of a wearable device technique that uses conductive yarn and flex sensor for measurement of elbow bending movements. Also this paper describes and discusses resistance value of zigzag embroidery of the conductive yarns on the tensile properties of the fabrics. Furthermore, by forming a circuit using an Arduino and flex sensor the prototype was created with an assistance band for golf posture training. This study provides valuable information to those interested in the future directions of the smart fashion industry.

• Journal of Korea Multimedia Society
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• v.19 no.3
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• pp.642-649
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• 2016

This paper presents a method for conversion of muscular sense into both visual and auditory senses based on synesthetic perception. Muscular sense can be defined by rotation angles, direction changes and motion degrees of human body. Synesthetic interconversion can be made by learning, so that it can be possible to create intentional synesthetic phenomena. In this paper, the muscular sense was converted into both color and sound signals which comprise the great majority of synesthetic phenomena. The measurement of muscular sense was performed by using the AHRS(attitude heading reference system). Roll, yaw and pitch signals of the AHRS were converted into three basic elements of color as well as sound, respectively. The proposed method was finally applied to a wearable device, Samsung gear S, successfully.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.12
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• pp.1815-1820
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• 2017

In this paper, a study was conducted to estimate the maximum muscle strength which is a standard for selecting exercise intensity in weight training. We designed a device that estimates the muscle fatigue from the EMG signal, expecting to show a correlation between peak muscle strength and fatigue. Curl - Dumbbell was performed using a 4 kg dumbbell and the frequency change of the EMG was observed. At this time, the designed device acquires the signal using the MCU and finally Matlab was used to confirm the change in the center frequency value. The results of 10 subjects were analyzed using SPSS regression analysis. The statistical results showed a correlation of $R^2$ 0.583 and Significant probability of 0.010, and the relation of Y = 8.144-2.097 (slope (MDF)) was obtained. In conclusion, if the wearable device is manufactured in the form of a wearable device and the user can recommend the exercise intensity, the system will be able to retry the more efficient exercise.