• International journal of advanced smart convergence
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• 제8권4호
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• pp.214-220
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• 2019

Hearing impaired people are apt to be in danger because they can't detect danger with sound. Hearing impaired people have less risk-detection ability than non-disabled people because of lack of hearing. There are many devices to help the hearing impaired, such as hearing aids. A hearing aids can be helpful, but it may not be available depending on the degree or type of hearing loss for example, to the hearing-impaired people with little remaining hearing of high frequencies, ordinary hearing aids are not very useful for understanding the high frequency consonants and it requires a high cost, from thousands to tens of thousands of dollars. Also, it is difficult for the underprivileged, such as the low-income bracket and the elderly, to use them because they are difficult to manage. Therefore, this paper describes the development of low-cost wearable device to assistant a hearing-impaired people using Arduino. Also, it accepts values from switches or sensors and can control external electronic devices such as LEDs and motors to create objects that can interact with the environment. In this is paper, through sound sensors, the ambient sound was taken as an analogue value and transmitted to the aduino board, and the vibration motor was operated when the noise was generated, so that the user could be aware of the occurrence of danger.

• 로봇학회논문지
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• 제9권3호
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• pp.133-139
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• 2014

This paper proposes a wearable and motorized crutch control system for the patients using the conventional crutches. The conventional crutches have a few disadvantages such as the inconvenience caused by the direct contact between the ground and the armpit of the patients, and unstable gait patterns. In order to resolve these problems, the motorized crutch is designed as a wearable type on an injured lower limb. In other words, the crutch makes the lower limb to be moved forward while supporting the body weight, protecting the lower limb with frames, and rotating a roller equipped on the bottom of the frames. Also the crutch is controlled using the electromyography and two force sensing resistor (FSR) sensors. The electromyography is used to extract the walking intention from the patient and the FSR sensors to classify the stance and swing phases while walking. As a result, the developed crutch makes the patients walk enabling both hands to be free, as if normal people do.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2138-2142
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• 2005

A wearable sensor system is proposed as a man-machine interface to control a device for walking assistance. The sensor system is composed of small sensors to detect the information about the user's body motion such as the activity level of skeletal muscles and the acceleration of each body parts. Each sensor includes a microcomputer and all the sensors are connected into a network by using the serial communication function of the microcomputer. The whole network is integrated into a belt made of soft fabric, thus, users can put on/off very easily. The sensor system is very reliable because of its decentralized network configuration. The body information obtained from the sensor system is used for controlling the assisting device to achieve a comfortable and an effective walking training.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권1호
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• pp.318-330
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• 2015

In wearable sensor systems (WSSs), sensor nodes are deployed around human body parts such as the arms, the legs, the stomach, and the back. These sensors have limited lifetimes because they are battery-operated. Thus, transmission power control (TPC) is needed to save the energy of sensor nodes. The TPC should control the transmission power level (TPL) of sensor nodes based on current channel conditions. However, previous TPC algorithms did not precisely estimate the channel conditions. Therefore, we propose a new TPC algorithm that uses an accelerometer to directly measure the current channel condition. Based on the directly measured channel condition, the proposed algorithm adaptively adjusts the transmission interval of control packets for updating TPL. The proposed algorithm is efficient because the power consumption of the accelerometer is much lower than that of control packet transmissions. To evaluate the effectiveness of our approach, we implemented the proposed algorithm in real sensor devices and compared its performance against diverse TPC algorithms. Through the experimental results, we proved that the proposed TPC algorithm outperformed other TPC algorithms in all channel environments.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 춘계학술대회
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• pp.141-143
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• 2021

The Activity patterns of animal species are difficult to access and the behavior of freely moving individuals can not be assessed by direct observation. As it has become large challenge to understand the activity pattern of animals such as dogs, and cats etc. One approach for monitoring these behaviors is the continuous collection of data by human observers. Therefore, in this study we assess the activity patterns of dog using the wearable sensors data such as accelerometer and gyroscope. A wearable, sensor -based system is suitable for such ends, and it will be able to monitor the dogs in real-time. The basic purpose of this study was to develop a system that can detect the activities based on the accelerometer and gyroscope signals. Therefore, we purpose a method which is based on the data collected from 10 dogs, including different nine breeds of different sizes and ages, and both genders. We applied six different state-of-the-art classifiers such as Random forests (RF), Support vector machine (SVM), Gradient boosting machine (GBM), XGBoost, k-nearest neighbors (KNN), and Decision tree classifier, respectively. The Random Forest showed a good classification result. We achieved an accuracy 86.73% while the detecting the activity.

• 한국멀티미디어학회논문지
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• 제23권9호
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• pp.1147-1154
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• 2020

Nowadays, one of the most common diseases is chronic mental fatigue syndrome. This can be caused by many factors, such as busy life, heavy workload, high population density, and adverse technological impact. Most office workers and students who are sitting all day long while being exposed to this kind of environments are likely to be involved in the mental illness. Therefore, to prevent the illness, it has been highly required to design a device that enables mental fatigue to be monitored continuously without human intervention. This paper proposes a linear regression method to reliably estimating the level of human mental fatigue using wearable physiological sensors, with an estimation error of 0.852. Also, this paper presents an Android application that is able to check mental health conditions in daily life.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1046-1048
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• 2003

Recently, various researches in respect of the positioning technologies using satellites and the other sensors have made location-based services (LBS) more common and accurate. Consequently, concern about position information has been increasing. However, since these positioning systems only focus on user's position, it is difficult to know the user's attitude or detailed behaviors at the specific position. It is worthy to study on how to acquire such human attitude or behavior, because those information is useful to know the context of the user. In this paper, the sensor unit consisting of three dimensional accelerometer was attached to human body, and autonomously measured the perpendicular acceleration of ordinary human behaviors including activity modes such as walking, running, and transportation mode using transportation such as a train, a bus, and an elevator. Subsequently, using the classified measurement results, the method to identify the human activity modes was proposed.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2019년도 춘계학술대회
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• pp.281-282
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• 2019

In recent years welfare of animals is the biggest challenge because animals, especially dogs are widely recognized as pet as well as they are using as service animals. So, for the wellbeing of the dog it is necessary to perform objective assessment to track their behavior in everyday life. In this paper, we have proposed an automatic behavior assessment system for dogs based on a neck worn and tail worn accelerometer and gyroscope platform, and data analysis techniques that recognize typical dog activities. We evaluate the system based on the analysis of 8 behavior traits in 3 dogs, incorporating 2 breeds of various sizes. Our proposed framework able to reproduce the manual assessment that is based on the video recording which is treated as gold standard that exhibits the real-life use case of automated dog behavior analysis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권5호
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• pp.998-1013
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• 2013

Wireless wearable sensor networks have emerged as a promising technique for human motion tracking due to the flexibility and scalability. In such system several wireless sensor nodes being attached to human limb construct a wearable sensor network, where each sensor node including MEMS sensors (such as 3-axis accelerometer, 3-axis magnetometer and 3-axis gyroscope) monitors the limb orientation and transmits these information to the base station for reconstruction via low-power wireless communication technique. Due to the energy constraint, the high fidelity requirement for real time rendering of human motion and tiny operating system embedded in each sensor node adds more challenges for the system implementation. In this paper, we discuss such challenges and experiences in detail during the implementation of such system with wireless wearable sensor network which includes COTS wireless sensor nodes (Imote 2) and uses TinyOS 1.x in each sensor node. Since our system uses the COTS sensor nodes and popular tiny operating system, it might be helpful for further exploration in such field.

• 한국정보과학회논문지:소프트웨어및응용
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• 제33권1호
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• pp.105-113
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• 2006

본 논문에서는 착용형 컴퓨팅을 위한 정형화된 컨텍스트 인식 응용 모형인 wear-UCAM (Unified Context-aware Application Model for Wearable Computing)을 제안한다. 유비쿼터스 컴퓨팅에 대한 관심이 고조되고 이와 함께 관련된 기술들이 발전함에 따라서, 언제 어디서나 손쉽게 컴퓨팅 자원을 활용할 수 있는 사용자 중심의 착용형 컴퓨팅에 관한 연구도 학계나 산업계에서도 활발히 진행 중이다. 제안된 wear-UCAM은 유비쿼터스 컴퓨팅 환경에서 사용자와 관련된 개인 정보를 센서로부터 획득하고 획득된 정보를 처리 및 분석해서 사용자의 컨텍스트에따른 개인화된 서비스를 제공할 수 있는 모델이다. 제안된 wear-UCAM의 특징은 다음과 같다. 1) 센서에서 획득된 정보로부터 사용자 정보 (User Profile)의 갱신, 2) 사용자의 생체 신호 수집 및 생체 신호 분석, 그리고 3) 다른 착용형 컴퓨터나 환경으로부터 사용자에 대한 개인 정보 보호이다. 본 논문에서 제안된 wear-UCAM은 컨텍스트 처리 과정의 추상화 및 센서와 응용 서비스간의 독립성 보장을 위한 다양한 컴포넌트들을 포함하고 있다. 따라서, 제안된 wear-UCAM은 유비쿼터스 컴퓨팅 환경에서 착용형 컴퓨팅에 필요한 사용자 중심의 컨텍스트기반 어플리케이션을 지원할 수 있는 모델이다. 본 논문에서는 제안된 wear-UCAM의 설계와 디자인된 wear-UCAM의 구체적인 구현 방법에 대해서 자세히 설명한다.