• Journal of the Korean Institute of Electrical and Electronic Material Engineers
• /
• v.29 no.5
• /
• pp.284-288
• /
• 2016

Among the various physiological information that could be obtained from human body, heartbeat rate is a commonly used vital sign in the clinical milieu. Photoplethysography (PPG) sensor is incorporated into many wearable healthcare devices because of its advantages such as simplicity of hardware structure and low-cost. However, healthcare device employing PPG sensor has been issued in susceptibility of light and motion artifact. In this paper, to develop the real-time heart rate measurement device that is less sensitive to the external noises, we have fabricated an ultra-small wireless LC resonant pressure sensor by MEMS process. After performance evaluation in linearity and repeatability of the MEMS pressure sensor, heartbeat waveform and rate on radial artery were obtained by using resonant frequency-pressure conversion method. The measured data using the proposed heartbeat rate measurement system was validated by comparing it with the data of an commercialized heart rate measurement device. Result of the proposed device was agreed well to that of the commercialized device. The obtained real time heartbeat wave and rate were displayed on personal mobile system by bluetooth communication.

• The Journal of Korea Robotics Society
• /
• v.18 no.4
• /
• pp.496-504
• /
• 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 the Korea Academia-Industrial cooperation Society
• /
• v.22 no.1
• /
• pp.18-23
• /
• 2021

There has been demand for many magnetic sensor applications, and to develop low-cost devices, it is critical to accurately understand the behavior of the magnetic field and the characteristics of magnetic sensors and target devices during initial development phase. The magnetic field has been known to have very complicated nonlinear data to calculate, so it has required expensive computing machines or research to accurately calculate the magnetic sensor values. However, this paper introduces a characteristic of a magnetic sensor called the giant magnetoresistance (GMR) and proposes simple and sufficient approaches to develop a wearable joystick device using a magnetic sensor. Particularly, this paper introduces the design factors for how to properly develop a low-cost wearable joystick device using magnetic sensors after carefully considering the mechanism of a real joystick and the characteristics of magnetic sensors. As a result, user test results are provided to show how users can operate this new wearable joystick device.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
• /
• v.36 no.1
• /
• pp.93-97
• /
• 2023

A triboelectric nanogenerator (TENG) is a device that converts mechanical energy into electrical energy, and has been considered as a substitute for continuous power supply due to its high performance, simple structure and eco-friendliness. Recently, it is important to develop a TENG using a non-toxic material in order to use it as a power source for wearable, attachable, and body-embeddable electronics. Here, we developed a human friendly TENG using polyvinyl chloride (PVC) gel containing acetyl tributyl citrate (ATBC), a non-toxic plasticizer. PVC gels were fabricated using various ratios of PVC and ATBC, and optimized by investigating dielectric properties, surface potential, output performance, and durability. The PVC gel based TENG generates output signals of 73 V and 4.3 μA, i.e., a 5-fold enhancement in the output power compared to pristine PVC-based TENG. In addition, the PVC gel can be stretched over 500% of strain. This study is expected to be helpful in the future development of non-toxic wearable TENG.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.12 no.4
• /
• pp.715-724
• /
• 2017

Today all kinds of smart devices are being developed with various researches on wearable devices that support smart computing on the human body. Skin diseases continue to rise including freckles, pimples, atopy, and scalp trouble due to the environmental and genetic factors, and people pay bigger medical bills to treat their skin diseases. There is thus a need to develop a smart-phone or table-based smart healthcare imaging system of high portability and diagnostic accuracy capable of analyzing and managing various skin problems related to skin care. This study proposed an integrated system combining the Smart Mi Band, a wearable device using moisture and UV sensors based on IoT, on the hardware part with the sensor information monitoring software.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.13 no.1
• /
• pp.221-228
• /
• 2018

Big data is an important keyword in World's Fourth Industrial Revolution in public and private division including IoT(Internet of Things), AI(Artificial Intelligence) and Cloud system in the fields of science, technology, industry and society. Big data based on services are available in various fields such as transportation, weather, medical care, and marketing. In particular, in the field of sports, various types of bio-signals can be collected and managed by the appearance of a wearable device that can measure vital signs in training or rehabilitation for daily life rather than a hospital or a rehabilitation center. However, research on big data with vital signs from wearable devices for training and rehabilitation for baseball players have not yet been stimulated. Therefore, in this paper, we propose a system for baseball infield and outfield players, especially which can store and analyze the momentum measurement vital signals based on big data.

• Journal of Sensor Science and Technology
• /
• v.21 no.4
• /
• pp.241-248
• /
• 2012

Recently healthcare industry such as pharmaceutical, medical device and healthcare service technology is growing significantly. Mobile healthcare has attracted big attention due to IT convergence technology. Paradigm of healthcare has been changed from the 1st generation(communicable disease prevention) and the 2nd generation(treatment of disease due to extended life expectancy) to the 3rd generation(extended life expectancy due to prevention and control). In our study, we suggest the 3rd generation mobile healthcare system using Bluetooth based wearable ECG monitoring system and smart phone technology. The mobile healthcare system consists of wearable shirts with Bluetooth communication module, ECG sensor, battery, and mobile phone. The ECG data is obtained by a miniaturized sensor and the data is transferred to a mobile phone using Bluetooth communication. Then, user can monitor his/her own ECG signal on an application using Android in mobile phone. The Bluetooth communication device is used due to highly reliable data transmission property and the Bluetooth chip is embedded in every mobile phone. The wearable shirts with chest belt of Bluetooth ECG module is designed with a focus on convenience in the daily life of a wearer. The ECG signal evaluation software in Android based mobile phone is developed for the health check and the ECG signal variation is tested according to the activities of the wearer such as walking, climbing stairs, stand up and sit down, and so on.

• Proceedings of the Korean Magnestics Society Conference
• /
• 2005.06a
• /
• pp.128-129
• /
• 2005

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.3 no.4
• /
• pp.43-48
• /
• 2010

The most problematic part in wearable terminals is the display device. To solve these problem, the HMD(Head Mounted Display) is used to wearable terminals. It is a kind of monitor worn like glasses. However, a problem exists in HMD. To select and execute the multimedia contents, it is required to manipulate the key, button, and mouse. These actions are very uncomfortable in HMD. The most fundamental way solving these problems is to develop a new interface. In this paper, we developed the wearable image watching system based on gesture recognition system.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.15 no.5
• /
• pp.205-214
• /
• 2020

With the recent development of hardware and software technology, interest in the development of wearable devices is increasing. In particular, wearable devices require algorithms suitable for low-power and low-capacity embedded devices. Among them, there is an increasing demand for a signal compression algorithm that reduces communication overhead, in order to increase the efficiency of storage and transmission of electrocardiogram (ECG) signals requiring long-time measurement. Because normal beats occupy most of the signal with similar shapes, a high rate of signal compression is possible if normal beats are represented by a template. In this paper, we propose an algorithm for determining the normal beat template using the template cluster and Pearson similarity. Also, the template is expressed effectively as a few vertices through linear approximation algorithm. In experiment of Datum 234 of MIT-BIH arrhythmia database (MIT-BIH ADB) provided by Physionet, a compression ratio was 33.44:1, and an average distribution of root mean square error (RMSE) was 1.55%.