• 한국멀티미디어학회논문지
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• 제19권5호
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• pp.808-817
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• 2016

Recently, the wearable computing technology with bio-sensors has been rapidly developed and utilized in various areas such as personal health, care-giving for senior citizens who live alone, and sports activities. In particular, the wearable computing equipment to measure vital signs by means of digital yarns and bio sensors is noticeable. The wearable computing devices help users monitor and manage their health in their daily lives through the customized healthcare service. In this paper, we suggest a system for monitoring and analyzing vital signs utilizing smart healthcare clothing with bio-sensors. Vital signs that can be continuously acquired from the clothing is well-known as unstructured data. The amount of data is huge, and they are perceived as the big data. Vital sings are stored by Hadoop Distributed File System(HDFS), and one can build data warehouse for analyzing them in HDFS. We provide health monitoring system based on vital sings that are acquired by biosensors in smart healthcare clothing. We implemented a big data platform which provides health monitoring service to visualize and monitor clinical information and physical activities performed by the users.

• 한국의류산업학회지
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• 제21권6호
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• pp.697-707
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• 2019

This review paper deals with materials, classification, and a current article investigation on smart textile sensors for wearable vital signs monitoring (WVSM). Smart textile sensors can lose electrical conductivity during vital signs monitoring when applying them to clothing. Because they should have to endure severe conditions (bending, folding, and distortion) when wearing. Imparting electrical conductivity for application is a critical consideration when manufacturing smart textile sensors. Smart textile sensors fabricate by utilizing electro-conductive materials such as metals, allotrope of carbon, and intrinsically conductive polymers (ICPs). It classifies as performance level, fabric structure, intrinsic/extrinsic modification, and sensing mechanism. The classification of smart textile sensors by sensing mechanism includes pressure/force sensors, strain sensors, electrodes, optical sensors, biosensors, and temperature/humidity sensors. In the previous study, pressure/force sensors perform well despite the small capacitance changes of 1-2 pF. Strain sensors work reliably at 1 ㏀/cm or lower. Electrodes require an electrical resistance of less than 10 Ω/cm. Optical sensors using plastic optical fibers (POF) coupled with light sources need light in-coupling efficiency values that are over 40%. Biosensors can quantify by wicking rate and/or colorimetry as the reactivity between the bioreceptor and transducer. Temperature/humidity sensors require actuating triggers that show the flap opening of shape memory polymer or with a color-changing time of thermochromic pigment lower than 17 seconds.

• 센서학회지
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• 제31권6호
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• pp.433-440
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• 2022

Recently, owing to global warming, average summer temperatures are increasing and the number of hot days is increasing is increasing, which leads to an increase in heat stroke. In particular, outdoor workers directly exposed to the heat are at higher risk of heat stroke; therefore, preventing heat-related illnesses and managing safety have become important. Although various wearable devices have been developed to prevent heat stroke for outdoor workers, applying various sensors to the safety helmets that workers must wear is an excellent alternative. In this study, we developed a smart helmet that measures various vital signs of the wearer such as body temperature, heart rate, and sweat rate; external environmental signals such as temperature and humidity; and movement signals of the wearer such as roll and pitch angles. The smart helmet can acquire the various data by connecting with a smartphone application. Environmental data can check the status of heat wave advisory, and the individual vital signs can monitor the health of workers. In addition, we developed an algorithm that classifies the risk of heat-related illness as normal and abnormal by inputting a set of vital signs of the wearer using a support vector machine technique, which is a machine learning technique that allows for rapid binary classification with high reliability. Furthermore, the classified results suggest that the safety manager can supervise the prevention of heat stroke by receiving feedback from the control system.

• 스마트미디어저널
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• 제3권4호
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• pp.35-40
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• 2014

바이오센서와 디지털 섬유의 개발로 생체신호를 측정할 수 있는 디지털 의류는 개인의 건강, 독거노인 관리와 스포츠 활동 등 여러 분야에서 사용할 수 있다. 본 논문은 디지털 의류를 착용하여 24시간 측정된 생체신호와 GPS 정보 기반의 사용자의 스트레스 상태, 맥박, 위치, 운동량을 분석하기 위한 데이터베이스 구조와 표준 HL7 메타모델기반의 XML 문서로 저장하는 저장소를 설계한다. 저장된 정보를 분석하여 사용자의 시간에 따른 스트레스 상태 및 운동량 등을 확인 할 수 있다. 또한, 실시간으로 사용자의 맥박, 위치, 운동 강도, 응급상황을 파악할 수 시스템이다. 본 논문은 생체신호를 수집하여 분석하는 시스템구현에 대하여 기술한다.

• Journal of Communications and Networks
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• 제17권4호
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• pp.419-427
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• 2015

There have been increases in the elderly population worldwide, and this has been accompanied by rapid growth in the health-care market, as there is an ongoing need to monitor the health of individuals. Wireless body area networks (WBANs) consist of wireless sensors attached on or inside the human body to monitor vital health-related problems, e.g., electrocardiograms (ECGs), electroencephalograms (EEGs), and electronystagmograms (ENGs). With WBANs, patients' vital signs are recorded by each sensor and sent to a coordinator. However, because of obstructions by the human body, sensors cannot always send the data to the coordinator, requiring them to transmit at higher power. Therefore, we need to consider the lifetime of the sensors given their required transmit power. In the IEEE 802.15.6 standard, the transmission topology functions as a one-hop star plus one topology. In order to obtain a high throughput, we reduce the transmit power of the sensors and maintain equity for all sensors. We propose the multiple-hop transmission for WBANs based on the IEEE 802.15.6 carrier-sense multiple-access with collision avoidance (CSMA/CA) protocol. We calculate the throughput and variance of the transmit power by performing simulations, and we discuss the results obtained using the proposed theorems.

• 한국산학기술학회논문지
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• 제18권5호
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• pp.86-92
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• 2017

고령화 인구 증가에 따른 만성질환자, 노약자 및 독거인의 일상생활에서 위험하거나 불안정한 건강 상태를 관리할 수 있는 요구가 커지고 있다. 최근 무선 통신 기술의 발달로 특정한 장소에 구애받지 않고 언제 어디서나 개인의 건강 상태를 감시할 수 있는 장치가 주목 받고 있다. 본 논문은 생체 신호로 심박수와 체온을 주기적으로 측정하고 밴드 착용자의 나이와 측정된 생체 신호를 토대로 건강관리가 필요함을 알리는 팔목형 건강관리용 밴드를 개발하는 것이 목적이다. 나이, 체온 및 심박수 사이의 정상 범위 관계는 비선형이고 측정된 생체 신호는 오차를 포함 부정확하기 때문에 생체 신호 기반의 건강관리 판정에는 부정확하고 애매한 정보의 처리가 필요하다. 본 논문은 이런 문제를 해결하기 위해 부정확하고 애매한 정보를 처리하는데 적합한 퍼지 논리 기반의 건강관리 판정 시스템을 밴드에 구현한다. 밴드에 연동해 동작하는 건강관리 앱(Apps)도 함께 개발된다. 앱은 측정 데이터를 저장, 관리하며 밴드에서 건강관리가 필요한 신호가 감지되면 앱에 사전 등록된 보호자 또는 간병인에게 해당 정보를 전송한다.

• International journal of advanced smart convergence
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• 제11권4호
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• pp.240-246
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• 2022

In order to measure the respiratory rate, one of the major vital signs, many devices have been developed and related studies have been conducted. In particular, as the number of wearers of respirators increases in the COVID-19 pandemic situation, studies have been conducted to measure the respiratory rate of the wearer by attaching an electronic sensor to the respirator, but most of them are cases in which an air flow sensor or a microphone sensor is used. In this study, we design and develop a system that measures the respiratory rate of the wearer using an air pressure sensor in a respirator. Air pressure sensors are inexpensive and consume less power than the other sensors. In addition, since the amount of data required for calculation is small and the algorithm is simple, it is suitable for small-scale and low-power processing devices such as Arduino. We developed an algorithm to measure the respiratory rate of a respirator wearer by analysing air pressure change patterns. In addition, variables that can affect air pressure changes were selected, and experimental scenarios were designed according to the variables. According to the designed scenario, we collected air pressure data while the respirator wearer was breathing. The performance of the developed system was evaluated using the collected data.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2012년도 추계학술대회
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• pp.154-156
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• 2012

This paper presents a user authentication scheme for healthcare application using wireless medical sensor networks, where wireless medical sensors are used for patients monitoring. These medical sensors' sense the patient body data and transmit it to the professionals (e.g., doctors, nurses, and surgeons). Since, the data of an individual are highly vulnerable; it must ensures that patients medical vital signs are secure, and are not exposed to an unauthorized person. In this regards, we have proposed a user1 authentication scheme for healthcare application using medical sensor networks. The proposed scheme includes: a novel two-factor professionals authentication (user authentication), where the healthcare professionals are authenticated before access the patient's body data; a secure session key is establish between the patient sensor node and the professional at the end of user authentication. Furthermore, the analysis shows that the proposed scheme is safeguard to various practical attacks and achieves efficiency at low computation cost.

• 센서학회지
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• 제19권6호
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• pp.435-442
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• 2010

Typically, the vital signs that are representing the state of human body, are the body temperature, sphygmus, respiration and blood pressure. The body temperature is the result of metabolic regulation and human steady-state body temperature is maintained from 35.9 to $37.4^{\circ}C$ by heat regulatory center. The body temperature is indicative of infection and especially it should be monitored to requiring intensive care patients or after surgical patients. But, measuring of body temperature to a heavy workload on nursing staff has been recognized. And, the health service of nurse is limited by simple tasks such as the measurement and record of vital sign. In this paper, the body temperature monitoring telemetry system was proposed to prove the recoding and transmission of body temperature patch system according the standard(ISO TS11073-92001). We proposed the transmission protocol to suit the MFER(medical waveform format encoding rules). The telemetry patch system was implemented and it was verified by experiments.

• 디지털정책학회지
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• 제2권4호
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• pp.25-32
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• 2023

논문은 PPG 기반 센서에서 측정한 심박수(HR), 심박변이도(HRV) 데이터를 기반으로 DNN(Deep Neural Network) 혈당예측 모델을 개발하는 연구이다. 혈당 예측은 다층퍼셉트론(MLP) 신경망을 이용하였다. DNN 심층학습은 11의 독립변수가 있는 입력층, 은닉층, 출력층으로 구성된다. 혈당 예측모델의 학습결과는 MAE=0.3781, MSE=0.8518, 및 RMSE=0.9229이며, 결정계수(R²)는 0.9994이다. PPG기반의 디지털기기를 이용한 비채혈적 생체신호를 이용하여 혈당관리의 가능성을 확인하였다. PPG기반의 표준화된 활력신호 획득 및 해석법, 다량의 데이터기반 심층학습(Deep Learning)의 데이터셋, 정확성를 실증하는 연구가 이어진다면 개의 혈당관리에 편이성과 대안적인 방법을 제공할 수 있을 것이다.