• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.300-302
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• 2021

Usage of a face mask has become mandatory in many countries after the COVID-19. This paper described to develop a IoT based smart mask system for monitoring face mask. The system developed in this paper has two main units, a sensor module, and a smartphone application. The sensor module consists of four components: temperature and humidity sensor, a heart rate sensor, and a BLE chip. This components work as a unit to collect data and stream them through an I2C port over BLE to a connected mobile device. The smartphone application is an Android application developed for smart phones. It enables the Android device to communicate with the sensor to receive sensor data, process, store and display results.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.2
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• pp.67-74
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• 2017

This paper proposes a method of user authentication through the patterns of arm movement with a wrist-type wearable device. Using the accelerometer sensor which is built in the device, the 3-axis accelerometer data are collected. Then, the collected data are integrated and the periodic cycle are extracted. In the cycle, the features of frequency are generated with the accelerometer. With the frequency features, 2D Gaussian mixture are modelled. For authenticating an user, the data(the accelerometer) of the user at some point are tested with confidence interval of the Gaussian distribution. The model showed a valuable results for the user authentication with an example, which is average 92% accuracy with 95% confidence interval.

• Journal of Internet Computing and Services
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• v.11 no.1
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• pp.129-141
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• 2010

In this paper, we present a wearable intelligent device based on multi-sensor for monitoring human activity. In order to recognize multiple activities, we developed activity recognition algorithms utilizing an image sensor and a 3-axis accelerometer sensor. We proposed a grid?based optical flow method and used a SVM classifier to analyze data acquired from multi-sensor. We used the direction and the magnitude of motion vectors extracted from the image sensor. We computed the correlation between axes and the magnitude of the FFT with data extracted from the 3-axis accelerometer sensor. In the experimental results, we showed that the accuracy of activity recognition based on the only image sensor, the only 3-axis accelerometer sensor, and the proposed multi-sensor method was 55.57%, 89.97%, and 89.97% respectively.

• Journal of Biomedical Engineering Research
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• v.28 no.2
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• pp.280-286
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• 2007

The wearable sensor glove was developed using EDA sensors and conducting fabric. EDA(Electro-dermal Activity) signal is an electric response of human skin. There are SIL(Skin Impedance Level) and SIR(Skin Impedance Response) in EDA. SIL consists mostly of a DC component while SIR consists of an AC component. The relationship between drowsiness and the EDA signal is utilized. EDA sensors were made using a conducting fabric instead of AgCl electrodes, for a more suitable, more wearable device. The EDA signal acquisition module was made by connecting the EDA sensor gloves through conductive fabric lines. Also, the EDA signal acquisition module can be connected to a PC that shows the results of the EDA signal processing analysis and gives proper feedback to the user. This system can be used in various applications to detect drowsiness and prevent accidents from drowsiness for automobile drivers.

• 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 the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.294-298
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• 2021

Recently, many electronic devices have been integrated with various kinds of wireless sensor network technologies that have been enabled with wireless network connections. These wireless sensor network devices have adopted various kinds of wireless network technologies. On the other hand, because each wireless network technology has its advantages and disadvantages, the target and purposes should be considered carefully at the beginning of the development. In particular, the approach to the magnetic sensor should be considered carefully because it has its own characteristic compared to general sensors. The magnetic field generates nonlinear data. This paper introduces the design aspects to reflect low cost and wearable devices to use in a wireless sensor network. In addition, this paper addresses how to select proper sensor network technology. As a result, wireless sensor network devices were integrated using Zigbee and showed the performance of the throughput.

• Journal of the Korea Society of Computer and Information
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• v.26 no.2
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• pp.125-132
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• 2021

In this paper, We propose a study on the construction of an environment for collaboration in mixed reality and a method for working with wearable IoT devices. Mixed reality is a mixed form of virtual reality and augmented reality. We can view objects in the real and virtual world at the same time. And unlike VR, MR HMD does not occur the motion sickness. It is using a wireless and attracting attention as a technology to be applied in industrial fields. Myo wearable device is a device that enables arm rotation tracking and hand gesture recognition by using a triaxial sensor, an EMG sensor, and an acceleration sensor. Although various studies related to MR are being progressed, discussions on developing an environment in which multiple people can participate in mixed reality and manipulating virtual objects with their own hands are insufficient. In this paper, We propose a method of constructing an environment where collaboration is possible and an interaction method for smooth interaction in order to apply mixed reality in real industrial fields. As a result, two people could participate in the mixed reality environment at the same time to share a unified object for the object, and created an environment where each person could interact with the Myo wearable interface equipment.

• The Journal of Korea Robotics Society
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• v.18 no.4
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• pp.496-504
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• 2023

This paper recognizes the motion intention of the wearer using a muscle stiffness sensor and proposes a control system for a wearable robot based on this. The proposed system recognizes the onset time of the motion using sensor data, determines the assistance mode, and provides assistive torque to the hip flexion/extension motion of the wearer through the generated reference trajectory according to the determined mode. The onset time of motion was detected using the CUSUM algorithm from the muscle stiffness sensor, and by comparing the detection results of the onset time with the EMG sensor and IMU, it verified its applicability as an input device for recognizing the intention of the wearer before motion. In addition, the stability of the proposed method was confirmed by comparing the results detected according to the walking speed of two subjects (1 male and 1 female). Based on these results, the assistance mode (gait assistance mode and muscle strengthening mode) was determined based on the detection results of onset time, and a reference trajectory was generated through cubic spline interpolation according to the determined assistance mode. And, the practicality of the proposed system was also confirmed by applying it to an actual wearable robot.

• Journal of Electrical Engineering and Technology
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• v.13 no.4
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• pp.1732-1739
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• 2018

With the explosion of digital devices, interaction technologies between human and devices are required more than ever. Especially, hand gesture recognition is advantageous in that it can be easily used. It is divided into the two groups: the contact sensor and the non-contact sensor. Compared with non-contact gesture recognition, the advantage of contact gesture recognition is that it is able to classify gestures that disappear from the sensor's sight. Also, since there is direct contacted with the user, relatively accurate information can be acquired. Electromyography (EMG) and force-sensitive resistors (FSRs) are the typical methods used for contact gesture recognition based on muscle activities. The sensors, however, are generally too sensitive to environmental disturbances such as electrical noises, electromagnetic signals and so on. In this paper, we propose a novel contact gesture recognition method based on Flexible Epidermal Tactile Sensor Array (FETSA) that is used to measure electrical signals according to movements of the wrist. To recognize gestures using FETSA, we extracted feature sets, and the gestures were subsequently classified using the support vector machine. The performance of the proposed gesture recognition method is very promising in comparison with two previous non-contact and contact gesture recognition studies.

• Journal of the Korea Fashion and Costume Design Association
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• v.19 no.4
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• pp.29-41
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• 2017

Because infants lack full communication skills and are not active main agents, nurturing and protection are essential. The value of smart devices that can help prevent potential threats and manage infant care is evaluated highly. This study offers basic research data that contributes to the development of devices for infant and parents as well as to future planning. This study compared and analyzed literature materials and visual materials based on news articles, advanced research, and official websites of brands. The research ranges and subjects are wearable devices for infants that were released or will be released between 2014 and 2017. Wearable devices that help protect and manage infant care are roughly separated into clothing, accessory, and the like. In this study, four kinds of clothing products, six kinds of accessories products, and fifteen kinds of other products were researched and a total of 25 kinds of products were analyzed. Categories was made in accordance with morphological characteristics, main features, materials and the design of wearable devices for infants depending on the device features. Wearable devices for infants that will be developed in the future must be based on a variety of suggestions in order to know best how to attach a sensor to an infant. From this study, the deduced trend analysis of wearable devices for infants can suggest new ways for follow-up studies as well as product development.