• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.275-282
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• 2024

This paper proposes an app-based feeder that performs functions such as distributing food and measuring exercise amount and a wearable collar that measures activity level to manage pet obesity in modern society where the obesity rate of pets is increasing. The wearable collar measures the pet's activity level and suggests the appropriate amount of food based on the average daily activity level. We studied an app-based pet feeding system that can provide the appropriate amount of feed per day through an app to enable obesity management even in unexpected situations.

• Science of Emotion and Sensibility
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• v.27 no.1
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• pp.59-68
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• 2024

This study aimed to develop a soft fabric-based elbow-bending angle sensor that can replace conventional hard-type inertial sensors and a system for estimating bending angles using it. To enhance comfort during exercise, this study treated four fabrics (Bergamo, E-band, span cushion, and polyester) by single-walled carbon nanotube dip coating to create conductive textiles. Subsequently, one fabric was selected based on performance evaluations, and an elbow flexion angle sensor was fabricated. Gauge factor, hysteresis, and sensing range were employed as performance evaluation metrics. The data obtained using the fabricated sensor showed different trends in sensor values for the changes in the angle during bending and extending movements. Because of this divergence, the two movements were separated, and this constituted the one-step process. In the two-step process, multilayer perceptron (MLP) was employed to handle the complex nonlinear relationships and achieve high data accuracy. Based on the results of this study, we anticipate effective utilization in various smart wearable and healthcare domains. Consequently, a soft- fabric bending angle sensor was developed, and using MLP, nonlinear relationships can be addressed, enabling angle estimation. Based on the results of this study, we anticipate the effective utilization of the developed system in smart wearables and healthcare.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.495-498
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• 2008

This paper describes design of a real-time, wearable reflectance pulse oximetry which is based Wireless Sensor Network. For the purpose of continuously monitoring vital signs of a human, wearable reflectance pulse oximetry is built into a wrist type that can be obtained $SpO_2$ value of patient unobtrusively. This designed $SpO_2$ module is based on a low-power 8 bit ATmega128L microcontroller operating in 3V. Low power operating $SpO_2$ module was integrated to wireless sensor node for user's health monitoring. This paper is focused on the successful integration of all these components into wearable reflectance pulse oximetry and evaluates its ability to measure patient' $SpO_2$ value. Information from this sensor was wirelessly transmitted to a base-station for storage and display purposes.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.06a
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• pp.278-279
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• 2016

최근 웨어러블 장치의 개발로 인하여 다양하게 생체 신호를 측정하는 방법이 많아지고 있다. 이와 관련하여 대표적으로 측정하는 신호가 PPG(plethysmography) 신호이다. PPG 신호를 이용하여 맥박수, 혈박출량, SPo2 등의 값들을 추정할 수 있다. 그러나 웨어러블 장치의 특성상 동적잡음이 많이 발생하게 된다. 동적잡음을 제거하기 위한 방법들은 가속도 센서를 사용하는 방법, 칼만필터(Kalman filter)를 이용하는 방법 등 다양한 방법들이 존재한다. 그러나 여전히 범용으로 사용하기에는 한계가 있다. 본 논문은 Neural Network를 사용하여 개인별로 PPG 신호를 학습하여 PPG 신호의 이상 유무를 판단하고 이전 신호의 평균 맥박수를 사용하여 효과적으로 PPG 신호의 정확한 맥박수를 검출하는 알고리듬을 제안한다.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2018.11a
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• pp.55-56
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• 2018

In order to reduce the risk of accidents, we proposed a construction safety management system combined with wearable device and LoRa (Low-Range Wireless Network) communication method to apply the usefulness of Internet (IoT) technology which means "everything connected". to construction safety management Management system. The proposed wearable safety device is a device that relays information exchange between wearable safety device and safety management server by LoRa wireless communication method. The safety management server can store workers bio-data and perform big data analysis. If a risk factor is determined from the analysis result, a warning is sent to the wearable safety device and the manager's application. The goal of this system is to prevent construction workers from entering the dangerous area that is not suitable for work, and to prevent safety accidents caused by human cause by detecting abnormal condition during work.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.5
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• pp.10-15
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• 2017

Research interest has strongly focused on developing a method for effectively transmitting bio-signals over a distance using a wireless wearable device. In this paper, we describe a procedure for the design and fabrication of a wearable antenna based on embroidering conductive threads to clothing capable of transmitting electrocardiogram signals. 3D electromagnetic simulation software and embroidery software were used to design and fabricate the conductive thread-based antenna, respectively. The measurement results show that the reflection coefficient of the fabricated antenna prototype exhibits excellent antenna impedance matching characteristics of less than -10dB in the Zigbee 2.4GHz frequency band. We also verified that the electrocardiogram data could be effectively received and monitored in real-time by a receiver 220m away from the transmitter.

• Journal of Korea Multimedia Society
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• v.15 no.7
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• pp.885-890
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• 2012

In this Paper, we propose a Real-Time Localization Platform Built on WUSB (Wireless USB) over WBAN (Wireless Body Area Networks) protocol required for Wearable Computer systems. Proposed Real-Time Localization Platform Technique is executed on the basis of WUSB over WBAN protocol at each sensor node comprising peripherals of a wearable computer system. In the Platform, a WUSB host calculates the location of a receiving sensor node by using the difference between the times at which the sensor node received different WBAN beacon frames sent from the WUSB host. And the WUSB host interprets motion of the virtual object.

• Journal of IKEEE
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• v.23 no.3
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• pp.844-851
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• 2019

As wearable technology is becoming more common and a part of our lives, there have been many efforts to offer various smart services with wearable devices, such as motion recognition, safety of driving, and so on. In this paper, we present a method that exploits the 9-axis inertial sensors embedded in a smartwatch to identify whether the user is a vehicle driver or not and to estimate the steering wheel turning direction in the vehicle. The system consists of three components: (i) position recognition, (ii) driver recognition, and (iii) steering-wheel turning detection components. We have developed a prototype system for detecting user's motion with Arduino boards and IMU sensors. Our experiments show high accuracy in recognizing the driver and in estimating the wheel rotation angle. The average experimental error was $11.77^{\circ}$ which is small enough to perceiver the turning direction of steering-wheel.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.1
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• pp.221-228
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• 2018

Big data is an important keyword in World's Fourth Industrial Revolution in public and private division including IoT(Internet of Things), AI(Artificial Intelligence) and Cloud system in the fields of science, technology, industry and society. Big data based on services are available in various fields such as transportation, weather, medical care, and marketing. In particular, in the field of sports, various types of bio-signals can be collected and managed by the appearance of a wearable device that can measure vital signs in training or rehabilitation for daily life rather than a hospital or a rehabilitation center. However, research on big data with vital signs from wearable devices for training and rehabilitation for baseball players have not yet been stimulated. Therefore, in this paper, we propose a system for baseball infield and outfield players, especially which can store and analyze the momentum measurement vital signals based on big data.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.3
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• pp.267-276
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• 2020

Manufacturing workers are easily exposed to the risk of musculoskeletal disorders caused by repetitive tasks in their working environment. This is due to problems with occupational characteristics that repeatedly use the body. However, the current lack of monitoring systems for monitoring and prevention has led to an increase in workers' exposure to risks each year. This paper presents how to solve these problems in real working environment by producing wearable devices using IMU sensors. After wearing a wearable type device, the user's movement is judged through data analysis by receiving the rotation value according to musculoskeletal movement. At this time, the risk is determined by measuring the number of rotations of the user by eliminating bias and eliminating cumulative error, acquiring sophisticated data, and analyzing it in the form of dynamic threshold values. Using the wearable device proposed in this paper, the effect of this method could be checked through a web page measuring the number of rotations for elbow musculoskeletal disorders.