• Applied Chemistry for Engineering
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• v.34 no.4
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• pp.347-356
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• 2023

Liquid crystal elastomer (LCE) fibers have been widely applied in various fields, such as soft robots and biomimetic actuators, in a one-dimensional form. LCEs possess the characteristics of both fluidity and solid order, as well as the elasticity of rubber, and exhibit stimulus-response based on these properties. In particular, by programming the responsiveness to various stimuli such as heat, light, electric fields, and magnetic fields in terms of shape-changing, various movements such as lifting, twisting, and rotating can be realized with high degrees of freedom. Therefore, LCE fibers have the potential for application in various fields such as artificial muscles, soft robots, wearable technologies, and sensing technologies. The research on liquid crystal elastomer fibers is evaluated to have high applicability in various fields in the Fourth Industrial Revolution as a smart material that can include various functionalities beyond simple fibers. In this review, we introduce the structure and basic characteristics of liquid crystal elastomer fibers, the latest research trends on orientation-based fabrication methods, and various applications such as artificial muscles, smart fabrics, and soft robots.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.37-44
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• 2023

As a primary technology of Industry 4.0, human-robot collaboration (HRC) requires additional measures to ensure worker safety. Previous studies on avoiding collisions between collaborative robots and workers mainly detect collisions based on sensors and cameras attached to the robot. This method requires complex algorithms to continuously track robots, people, and objects and has the disadvantage of not being able to respond quickly to changes in the work environment. The present study was conducted to implement a web-based platform that manages collaborative robots by recognizing the emotions of workers - specifically their perception of danger - in the collaborative process. To this end, we developed a web-based application that collects and stores emotion-related brain waves via a wearable device; a deep-learning model that extracts and classifies the characteristics of neutral, positive, and negative emotions; and an Internet-of-things (IoT) interface program that controls motor operation according to classified emotions. We conducted a comparative analysis of our system's performance using a public open dataset and a dataset collected through actual measurement, achieving validation accuracies of 96.8% and 70.7%, respectively.

• Electronics and Telecommunications Trends
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• v.34 no.5
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• pp.48-57
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• 2019

As the super-aged society approaches rapidly, the number of people suffering from post-stroke and other neurological disorders is significantly increasing, where prompt and intensive rehabilitation is essential for such people to resume their physical activities in normal daily lives. To overcome the inherent limitations of manual physical therapy, various types of exoskeleton robots are being employed. However, the need of the hour is softer, thinner, lighter, and even stretchable systems for precisely monitoring the motion of each joint without restricting the patients' movements in rehabilitation tasks. In this paper, we discuss the technological trends and current status of emerging stretchable rehabilitation systems, in which sensors, interconnects, and signal-processing circuits are monolithically integrated within a single stretchable substrate attachable to the skin. Such skin-like stretchable rehabilitation devices are expected to provide much more convenient, user-friendly, and motivating rehabilitation to patients with neurological impairments.

• Journal of Sensor Science and Technology
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• v.32 no.1
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• pp.22-30
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• 2023

Innovative and advanced technologies, including robots, augmented reality, virtual reality, the Internet of Things, and wearable medical equipment, have largely emerged as a result of the rapid evolution of modern society. For these applications, pressure monitoring is essential and pressure sensors have attracted considerable interest. To improve the sensor performance, several new designs of pressure sensors have been researched based on resistive, capacitive, piezoelectric, optical, and triboelectric types. In particular, optical pressure sensors have been actively studied owing to their advantages, such as robustness to noise and remote sensing capability. Herein, a review of recent research on optical pressure sensors with self-powered sensing, remote sensing, high spatial resolution, and multimodal sensing capabilities is presented from the viewpoints of design, fabrication, and signal processing.

• Journal of Digital Convergence
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• v.16 no.8
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• pp.129-136
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• 2018

This study analyzed technology application field and technology transfer type related to the 4th industrial revolution using frequency, visualization, and association analysis of text mining of Big Data. The analysis was conducted between the last three years (2015 - 2017) registered with the NTB of KIAT transfer technology database was utilized. As a result of analysis, First, First, transfer technologies called core technologies of the Fourth Industrial Revolution are a lot of about robots, 3D, autonomous driving, and wearables. Second, as the year go by, transfer technolgy registration such as IoT, Cloud, VR is increasing. Third, the results of the association analysis of technology transfer type are as follows. IoT and VR showed preference for technology trading and licensing, autonomous driving technology trading, wearable licensing, robots preferring technology cooperation, licensing, and technology trading.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.8
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• pp.771-782
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• 2017

This paper describes the development of a wearable robot to assist ankle power for the elderly. Previously developed wearable robots have generally used motors and gears to assist muscle power during walking. However, the combination of motor and reduction gear is heavy and has limitations on the simultaneous control of stiffness and torque due to the friction of the gear reducer unlike human muscles. Therefore, in this study, Mckibben pneumatic muscle, which is lighter, safer, and more powerful than an electric motor with gear, was used to assist ankle joint. Antagonistic actuation using a pair of pneumatic muscles assisted the power of the soleus muscles and tibialis anterior muscles used for the pitching motion of the ankle joint, and the model parameters of the antagonistic actuator were experimentally derived using a muscle test platform. To recognize the wearer's walking intention, foot load and ankle torque were calculated by measuring the pressure and the center of pressure of the foot using force and linear displacement sensors, and the stiffness and the torque of the pneumatic muscle joint were then controlled by the calculated ankle torque and foot load. Finally, the performance of the developed ankle power assistive robot was experimentally verified by measuring EMG signals during walking experiments on a treadmill.

• Transactions of the KSME C: Technology and Education
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• v.5 no.1
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• pp.1-6
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• 2017

From early simple bulky detectors to show the existence of some specific material, sensor has been developed to miniature smart sensors embedded signal capabilities with a help of nano/micro engineering such as innovative nano materials and semiconductor process technologies. Due to recently fast sales of smart phones with simple telephone function plus many sensors, internet accessing capabilities, easy user downloadable "app" softwares, smart sensor industry market has expanded very fast. If driver-less cars, wearable electronic devices and smart robots will be introduced into market in near future, development of many various smart sensors will be needed.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.3
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• pp.701-707
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• 2024

Industry 4.0 has brought about significant changes in the roles of workers through the introduction of innovative technologies. In smart factory environments, workers are required to interact seamlessly with robots and automated systems, often utilizing equipment enhanced by Virtual Reality (VR) and Augmented Reality (AR) technologies. This study aims to systematically analyze recent research literature on monitoring the physical and mental states of workers in Industry 4.0 environments. Relevant literature was collected using the Web of Science database, employing a comprehensive keyword search strategy involving terms related to Industry 4.0 and health monitoring. The initial search yielded 1,708 documents, which were refined to 923 journal articles. The analysis was conducted using VOSviewer, a tool for visualizing bibliometric data. The study identified general trends in the publication years, countries of authors, and research fields. Keywords were clustered into four main areas: 'Industry 4.0', 'Internet of Things', 'Machine Learning', and 'Monitoring'. The findings highlight that research on health monitoring of workers in Industry 4.0 is still emerging, with most studies focusing on using wearable devices to monitor mental and physical stress and risks. This study provides a foundational overview of the current state of research on health monitoring in Industry 4.0, emphasizing the need for continued exploration in this critical area to enhance worker well-being and productivity.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.868-871
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• 2016

Recently, Unmanned vehicle and Wearable Technology using iot research is being carried out. The unmanned vehicle is the result of it technology. Robots, autonomous navigation vehicle and obstacle avoidance, data communications, power, and image processing, technology integration of a unmanned vehicle or an unmanned robot. The final goal of the unmanned vehicle manual not autonomous by destination safely and quickly reaching. This paper managed to cover One of the key skills of unmanned vehicle is to image processing. Currently battery technology of unmanned vehicle can drive for up to 1 hours. Therefore, we use the Raspberry Pi 3 to reduce power consumption to a minimum. Using the Raspberry Pi 3 and to develop an image recognition system. The goal is to propose a system that recognizes all the objects in the image received from the camera.