• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.757-770
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• 2020

We propose a hand gesture recognition method that is compatible with a head-up display (HUD) including small processing resource. For fast link adaptation with HUD, it is necessary to rapidly process gesture recognition and send the minimum amount of driver hand gesture data from the wearable device. Therefore, we use a method that recognizes each hand gesture with an inertial measurement unit (IMU) sensor based on revised correlation matching. The method of gesture recognition is executed by calculating the correlation between every axis of the acquired data set. By classifying pre-defined gesture values and actions, the proposed method enables rapid recognition. Furthermore, we evaluate the performance of the algorithm, which can be implanted within wearable bands, requiring a minimal process load. The experimental results evaluated the feasibility and effectiveness of our decomposed correlation matching method. Furthermore, we tested the proposed algorithm to confirm the effectiveness of the system using pre-defined gestures of specific motions with a wearable platform device. The experimental results validated the feasibility and effectiveness of the proposed hand gesture recognition system. Despite being based on a very simple concept, the proposed algorithm showed good performance in recognition accuracy.

• Journal of the Korean Society of Safety
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• v.35 no.2
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• pp.94-99
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• 2020

Bikers can be subjected to injuries from unexpected accidents even if they wear basic helmets. A properly designed airbag can efficiently protect the critical areas of the human body. This study introduces a wearable smart airbag system using machine learning techniques to protect human neck and shoulders. When a bicycle accident happens, a microprocessor analyzes the biker's motion data to recognize if it is a critical accident by comparing with accident classification models. These models are trained by a variety of possible accidents through machine learning techniques, like k-means and SVM methods. When the microprocessor decides it is a critical accident, it issues an actuation signal for the gas inflater to inflate the airbag. A protype of the wearable smart airbag with the machine learning techniques is developed and its performance is tested using a human dummy mounted on a moving cart.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.664-667
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• 2009

There is strong demand to create wearable PC systems that can support the user outdoors. When we are outdoors, our movement makes it impossible to use traditional input devices such as keyboards and mice. We propose a hand gesture interface based on image processing to operate wearable PCs. The semi-transparent PC screen is displayed on the head mount display (HMD), and the user makes hand gestures to select icons on the screen. The user's hand is extracted from the images captured by a color camera mounted above the HMD. Since skin color can vary widely due to outdoor lighting effects, a key problem is accurately discrimination the hand from the background. The proposed method does not assume any fixed skin color space. First, the image is divided into blocks and blocks with similar average color are linked. Contiguous regions are then subjected to hand recognition. Blocks on the edges of the hand region are subdivided for more accurate finger discrimination. A change in hand shape is recognized as hand movement. Our current input interface associates a hand grasp with a mouse click. Tests on a prototype system confirm that the proposed method recognizes hand gestures accurately at high speed. We intend to develop a wider range of recognizable gestures.

• Korean Journal of Applied Biomechanics
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• v.29 no.1
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• pp.1-8
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• 2019

Objective: The purpose of this study was to confirm that the cross-country ski sprint course in PyeongChang, where the 2018 Winter Olympics course was to utilize wearable devices equipped with inertial measurement unit (IMU), global positioning system (GPS) and heart rates sensor. Method: For the data collection, two national level cross-country (XC) skiers performed classic technique on the entire sprint course. We analyzed cycle characteristics, range of motion on double poling (DP) technique, average velocity, and displacement of 3 points according to the terrain. Results: The absolute cycle time gradually decreased during starting, middle and finish sections. While the length of the DP increased and the heart rates tended to increase for men skier. In addition, the results indicated that range of motion of knee joint during starting and finish section decreased more than middle section. The errors of latitude and longitude data collected through GPS were within 3 m from 3 points. Conclusion: Through the first case study in Korea, which analyzed the location and condition of XC skiers in the entire sprint course in real time, confirmed that feedback was available in the field using various wearable sensors.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.1
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• pp.19-24
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• 2022

Through the development and dissemination of embedded devices, studies that may help patients are rapidly emerging. Recently, as wearable devices have become one of the ways to diagnose diseases in daily life, they are being studied as a way to assist severely ill patients to lead their daily lives. Among them, a method of detecting and giving signals to detect and solve symptoms using acceleration sensors to diagnose Parkinson's disease is being studied, and there is no study to measure and analyze various factors that can affect Parkinson's disease. To solve them, we designed and developed a wearable device, P-Band, with various sensors capable of diagnosing related symptoms, including acceleration sensors capable of diagnosing Parkinson's disease. In this paper, the overall structure of the P-Band and the description and operation method of the measurable sensors are presented. In addition, it was confirmed that the symptoms of Parkinson's patients could be determined complexly through the results measured in actual patients.

• Journal of Sensor Science and Technology
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• v.31 no.5
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• pp.301-306
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• 2022

With the recent widespread implementation of Internet of Things (IoT) technology driven by Industry 4.0, self-powered sensors for wearable and implantable systems are increasingly gaining attention. Piezoelectric nanogenerators (PENGs) and triboelectric nanogenerators (TENGs), which convert biomechanical energy into electrical energy, can be considered as efficient self-powered sensor platforms. These are energy harvesters that are used as low-power energy sources. However, they can also be used as sensors when an output signal is used to sense any mechanical stimuli. For sensors, collecting high-quality data is important. However, the accuracy of sensing for practical applications is equally important. This paper provides a brief review of the performance advanced by the materials and structures of the latest PENG/TENG-based wearable sensors and intelligent applications applied using artificial intelligence (AI)

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.5
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• pp.1087-1095
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• 2014

A recent major development in computer technology is the advent of the wearable computer system that is based on human-centric interface technology trends and ubiquitous computing environments. Wearable computer systems can use the wireless universal serial bus (WUSB) that refers to USB technology that is merged with WiMedia PHY/MAC technical specifications. In this paper, we focus on an integrated system of the wireless USB over the IEEE 802.15.6 wireless body area networks (WBAN) for wireless wearable computer systems supporting U-health services. And a communication structure that can differentiate QoS of U-health WBAN and WUSB traffic with different priorities is proposed for WUSB over IEEE 802.15.6 hierarchical protocol. In our proposal and performance evaluation, throughputs of U-health WBAN and WUSB traffic are analyzed under single and multiple QoS classes to evaluate the effectiveness of proposed QoS differentiating structure in WUSB over IEEE 802.15.6.

• Information Systems Review
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• v.24 no.3
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• pp.23-41
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• 2022

This case research investigates on how hearing aids, which is one of disability aids, is becoming a smart device, focusing on the case of Starkey Hearing Technologies(Starkey Inc.). Starkey, founded in 1967, has been a leader in innovating forms and functions of hearing aids, and has recently introduced the world's first hearing aid implemented with AI and biological sensors. In this study, history of disability aids, hearing aids(especially Starkey Inc.'s), smart wearable devices and smart earphones are compared. It has been found that recently, there has been a breakdown of boundaries between hearing aids and smart wearable devices in terms of their functions, since entertainment and life assistant functions are added to hearing aids. Based on this trend, the development model of disability aids and smart wearable devices are derived, and according social changes are discussed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.6
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• pp.1478-1499
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• 2024

Coronavirus disease (COVID-19) is an infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. COVID-19 become an active epidemic disease due to its spread around the globe. The main causes of the spread are through interaction and transmission of the droplets through coughing and sneezing. The spread can be minimized by isolating the susceptible patients. However, it necessitates remote monitoring to check the breathing issues of the patient remotely to minimize the interactions for spread minimization. Thus, in this article, we offer a wearable-IoTs-centered framework for remote monitoring and recognition of the breathing pattern and abnormal breath detection for timely providing the proper oxygen level required. We propose wearable sensors accelerometer and gyroscope-based breathing time-series data acquisition, temporal features extraction, and machine learning algorithms for pattern detection and abnormality identification. The sensors provide the data through Bluetooth and receive it at the server for further processing and recognition. We collect the six breathing patterns from the twenty subjects and each pattern is recorded for about five minutes. We match prediction accuracies of all machine learning models under study (i.e. Random forest, Gradient boosting tree, Decision tree, and K-nearest neighbor. Our results show that normal breathing and Bradypnea are the most correctly recognized breathing patterns. However, in some cases, algorithm recognizes kussmaul well also. Collectively, the classification outcomes of Random Forest and Gradient Boost Trees are better than the other two algorithms.

• Journal of Convergence Society for SMB
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• v.3 no.2
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• pp.27-32
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• 2013

Wireless Body Area Networks (WBAN) have been made possible by the emergence of small and lightweight wireless systems such as Bluetooth, enabled devices and PDAs. Antennas are an essential part of any WBAN system and due to various technical requirements and physical constraints, careful consideration of their design and deployment is needed. This paper is proposing on the design of wearable antenna as parts of clothing to serve communications functions, such as tracking and navigation in health care applications. The substrates of the wearable antennas will be made from textile materials and since it is wearable, it should have a small size, be light weight, low maintenance, and unobtrusive. This proposed paper will also investigate the influence of different parameters for wearable antenna including types of textile/substrate to ensure that the antenna design satisfies WBAN requirements. The characteristics and behavior of the antenna need to adhere to specifications set by wireless standards and system technology requirements. This means that the transmitting and receiving frequency bands of the various units need to be chosen accordingly. Since there are restrictions on the level of power to which the human body can be exposed to, the antenna as well as other RF system components must be designed to meet these restrictions. Antenna gain, which directly affects power transmitted, is a critical parameter in ensuring power levels fall within the safety guidelines and so will be of primary importance in the design. The electromagnetic interaction between WBAN antennas and devices and the human body will also be explored.