• Journal of Sensor Science and Technology
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• v.28 no.3
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• pp.198-204
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• 2019

In this study, we propose a wearable force sensor using 3D printed mold and liquid metal. Liquid metal, such as Galinstan, is one of the promising functional materials in stretchable electronics known for its intrinsic mechanical and electronic properties. The proposed soft force sensor measures the external force by the resistance change caused by the cross-sectional area change. Fused deposition modeling-based 3D printing is a simple and cost-effective fabrication of resilient elastomers using liquid metal. Using a 3D printed microchannel mold, 3D multichannel Galinstan microchannels were fabricated with a serpentine structure for signal stability because it is important to maintain the sensitivity of the sensor even in various mechanical deformations. We performed various electro-mechanical tests for performance characterization and verified the signal stability while stretching and bending. The proposed sensor exhibited good signal stability under 100% longitudinal strain, and the resistance change ranged within 5% of the initial value. We attached the proposed sensor on the finger joint and evaluated the signal change during various finger movements and the application of external forces.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.510-512
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• 2019

Recently, there have been growing requirements in the public safety sector to ensure safety through detection of hazardous situations or preemptive predictions. It is noteworthy that various sensor data can be analyzed and utilized as a result of mobile device's dissemination, and many advantages can be used in terms of safety and security. An effective modeling technique is needed to combine sensor data generated by smart-phones and wearable devices to analyze users' moving patterns and behavioral patterns, and to ensure public safety by fusing location-based crime risk data provided.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.9
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• pp.1224-1230
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• 2020

Since the spread of smart phones, interest in wearable devices has increased and diversified, and is closely related to the lives of users, and has been used as a method for providing personalized services. In this paper, we propose a method to detect the user's behavior by applying information from a 3-axis acceleration sensor and a 3-axis gyro sensor embedded in a smartphone to a convolutional neural network. Human behavior differs according to the size and range of motion, starting and ending time, including the duration of the signal data constituting the motion. Therefore, there is a performance problem for accuracy when applied to a convolutional neural network as it is. Therefore, we proposed a Time-Division Feature Fusion Convolutional Neural Network (TDFFCNN) that learns the characteristics of the sensor data segmented over time. The proposed method outperformed other classifiers such as SVM, IBk, convolutional neural network, and long-term memory circulatory neural network.

• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.39-46
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• 2021

In this paper, we propose a method for the motion recognition method required in the industrial field in mixed reality. In industrial sites, movements (grasping, lifting, and carrying) are required throughout the upper full-body, from trunk movements to arm movements. In this paper, we use a method composed of sensors and wearable devices that are not vision-based such as Kinect without using heavy motion capture equipment. We used two IMU sensors for the trunk and shoulder movement, and used Myo arm band for the arm movements. Real-time data coming from a total of 4 are fused to enable motion recognition for the entire upper body area. As an experimental method, a sensor was attached to the actual clothes, and objects were manipulated through synchronization. As a result, the method using the synchronization method has no errors in large and small operations. Finally, through the performance evaluation, the average result was 50 frames for single-handed operation on the HoloLens and 60 frames for both-handed operation.

• Journal of the Microelectronics and Packaging Society
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• v.28 no.4
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• pp.73-77
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• 2021

Flexible electrodes for wearable devices have been actively studied in not only achieving mechanical/electrical stability, but also providing various functionalities for extending its industrial application. In this study, a flexible carbon/PDMS composite is prepared by addition of carbon black (CB) as a conductive filler, and effect of CB with different contents on electrical properties of the composite was investigated for the application of flexible electrodes, temperature sensor and heater. With increase of CB contents, resistivity of the carbon/PDMS was increased, and excellent durability was observed, confirmed by repetitive stretching deformation test. Resistance increase of the carbon/PDMS with temperature reveals the property of positive temperature coefficient, which can be applied for temperature sensor. Also, joule heating on the carbon/PDMS was observed when electrical potential was applied, indicating the applicability of the carbon/PDMS for heater.

• Journal of Fashion Business
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• v.27 no.4
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• pp.125-140
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• 2023

This study aimed to develop a smart wearable device for assessing the risk angle associated with turtle neck syndrome in patients with Video Display Terminal (VDT) syndrome. Turtle neck syndrome, characterized by forward head posture resulting from upper cross syndrome, leads to thoracic kyphosis. In this research, a stretch sensor was used to monitor the progression of turtle neck syndrome, and the sensor data was analyzed using a Universal Testing Machine (UTM) and the Gauge Factor (GF) calculation method. The scapula and cervical spine angles were measured at five stages, with 15-degree increments from 0° to 60°. During the experimental process, the stretch sensor was attached to the thoracic spine in three different lengths: 30mm, 50mm, and 100mm. Among these, the attachment method yielding the most reliable data was determined by measuring with three techniques (General Trim Adhesive, PU film, and Heat Transfer Machine), and clothing using the heat transfer machine was selected. The experimental results confirmed that the most significant change in thoracic kyphosis occurred at approximately 30° of forward head posture. Prolonged deformity can lead to various issues, highlighting the need for textile sensor solutions. The developed wearable device aims to provide users with real-time feedback on their turtle neck posture and incorporate features that can help prevent or improve the condition.

• Journal of Korea Multimedia Society
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• v.21 no.8
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• pp.982-990
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• 2018

In recent years, many wearable devices and mobile apps related to life care have been developed, and a service for measuring the movement during walking and showing the amount of exercise has been provided. However, they do not measure walking in detail, so there may be errors in the total calorie consumption. If the user's behavior is measured by a multi-axis sensor and learned by a machine learning algorithm to recognize the kind of behavior, the detailed operation of walking can be autonomously distinguished and the total calorie consumption can be calculated more than the conventional method. In order to verify this, we measured activities and created a model using a machine learning algorithm. As a result of the comparison experiment, it was confirmed that the average accuracy was 12.5% or more higher than that of the conventional method. Also, in the measurement of the momentum, the calorie consumption accuracy is more than 49.53% than that of the conventional method. If the activity recognition is performed using the wearable device and the machine learning algorithm, the accuracy can be improved and the energy consumption calculation accuracy can be improved.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.585-590
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• 2007

최근 IT기술의 비약적인 발전과 더불어 사용자의 편의성을 극대화 시키는 웨어러블 컴퓨팅 기술이 주목을 받고 있다. 이러한 기술은 일반인뿐만 아니라 장애인들의 일상생활의 보조 도구에 활용되어 큰 도움이 될 것으로 예상된다. 본 논문에서는 시각 및 청각장애인을 위해 개발된 착용형 단말기들을 소개하고자 한다. 시각 장애인용 단말기인 SmartWand는 시각장애인용 지팡이에 부착하거나 손에 휴대할 수 있는 장치로, 시작장애인을 위한 보행 보조 및 색상과 명암 정보 인식 보조 기능을 갖춘 장치이다. SmarWand는 시각장애인이 보행 시 이용하는 기존의 지팡이로는 감지할 수 없는 전방의 장애물을 초음파 센서를 통해 탐지하여 촉각이나 음성으로 경고해주고, 물체의 색깔이나 주변의 밝기 정도를 측정하여 시각장애인에게 알려준다. 청각 장애인용 단말기인 SmarWatch는 손목에 착용하는 장치로서 아기 울음소리, 노크나 초인종 소리, 물 끓는 소리, 화재 경보 등 가정에서 발생하는 일상적인 소리를 인식할 수 있도록 해준다. SmartWatch는 입력 모듈의 마이크로 입력된 소리를 문선통신을 통해 컴퓨터로 전송한 후에 소리의 종류를 인식하고 적절한 제어신호를 다시 무선통신을 통해 전송받아 감지된 소리의 종류를 해당하는 진동과 시각정보로 표시해준다. 이런 착용형 단말기들을 통해 시각 및 청각 장애인의 일상 생활의 안정성과 편의성이 증대 되기를 기대한다.

• The Research Journal of the Costume Culture
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• v.25 no.4
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• pp.529-542
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• 2017

The purpose of this study is to utilize technology as basic data for smart clothing product research and development. This technology can recognize user's motion according to characteristics types and functions of wearable smart clothing products. In order to analyze the case of motion recognition products, we searched for previous research data and cases referred to as major keywords in leading search engines, Google and Naver. Among the searched cases, information on the characteristics and major functions of the 42 final products selected on the market are examined in detail. Motion recognition for smart clothing products is classified into four body types: head & face, body, arms & hands, and legs & feet. Smart clothing products was developed with various items, such as hats, glasses, bras, shirts, pants, bracelets, rings, socks, shoes, etc., It was divided into four functions health care type for prevention of injuries, health monitor, posture correction, sports type for heartbeat and exercise monitor, exercise coaching, posture correction, convenience for smart controller and security and entertainment type for pleasure. The function of the motion recognition smart clothing product discussed in this study will be a useful reference when designing a motion recognition smart clothing product that is blended with IT technology.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.947-948
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• 2015

IOT(Internet of things) is a technology to embed various sensors and communication features on diverse things such as home appliances, mobile devices, wearable computers and connect to the Internet and through this technology, the status of things connected to the network can be analyzed and controlled with various data. On the other hand, this paper suggests to develop a merchandise management app using Android-based barcode to systematically manage expiry date of various goods that we purchase in our daily life. Therefore, individual goods are recognized with mobile-based barcode and divided under each category. By additionally supporting the notification service to let us know about expire date, goods can be efficiently managed.