• Journal of electromagnetic engineering and science
• /
• v.13 no.1
• /
• pp.28-33
• /
• 2013

This paper proposes a miniaturized high-isolation diversity antenna for wearable wireless body area network (WBAN) applications. An inverted-F type radiating element is used to reduce the overall dimension of the proposed antenna to $30mm{\times}30mm{\times}2.5mm$. The antenna performance on the human body phantom is analyzed through simulation and the performance of the fabricated antenna is verified by comparing the measured data with that of the simulation when the antenna is placed on a semi-solid flat phantom with equivalent electrical properties of a human body. The fabricated antenna has a 10 dB return loss bandwidth over the Industrial Scientific Medical (ISM) band from 2.35 GHz to 2.71 GHz and isolation is higher than 28 dB at 2.45 GHz. The measured peak gain of antenna elements # 1 and # 2 is -0.43 dBi and -0.54 dBi, respectively. Performance parameters are analyzed, including envelope correlation coefficient (ECC), mean effective gain (MEG), and the MEG ratio. In addition, the specific absorption ratio (SAR) distributions of the proposed antenna are measured for consideration in use.

• 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.

• Journal of Electrical Engineering and Technology
• /
• v.12 no.1
• /
• pp.317-328
• /
• 2017

This paper presents design and specific absorption rate analysis of a 2.4 GHz wearable patch antenna on a conventional and electromagnetic bandgap (EBG) ground planes, under normal and bent conditions. Wearable materials are used in the design of the antenna and EBG surfaces. A woven fabric (Zelt) is used as a conductive material and a 3 mm thicker Wash Cotton is used as a substrate. The dielectric constant and tangent loss of the substrate are 1.51 and 0.02 respectively. The volume of the proposed antenna is $113{\times}96.4{\times}3mm^3$. The metamaterial surface is used as a high impedance surface which shields the body from the hazards of electromagnetic radiations to reduce the Specific Absorption Rate (SAR). For on-body analysis a three layer model (containing skin, fats and muscles) of human arm is used. Antenna employing the EBG ground plane gives safe value of SAR (i.e. 1.77W/kg<2W/kg), when worn on human arm. This value is obtained using the safe limit of 2 W/kg, averaged over 10g of tissue, specified by the International Commission of Non Ionization Radiation Protection (ICNIRP). The SAR is reduced by 83.82 % as compare to the conventional antenna (8.16 W/kg>2W/kg). The efficiency of the EBG based antenna is improved from 52 to 74 %, relative to the conventional counterpart. The proposed antenna can be used in wearable electronics and smart clothing.

• Journal of the Ergonomics Society of Korea
• /
• v.30 no.1
• /
• pp.229-235
• /
• 2011

Objective: Making a new ergonomic interface system based on camera vision system, which helps the handicapped in home environment. Background: Enabling the handicapped to manipulate the consumer electronics by the proposed interface system. Method: A wearable device for capturing the eye image using a near-infrared(NIR) camera and illuminators is proposed for tracking eye gaze position(Heo et al., 2011). A frontal viewing camera is attached to the wearable device, which can recognize the consumer electronics to be controlled(Heo et al., 2011). And the amount of user's eye fatigue can be measured based on eye blink rate, and in case that the user's fatigue exceeds in the predetermined level, the proposed system can automatically change the mode of gaze based interface into that of manual selection. Results: The experimental results showed that the gaze estimation error of the proposed method was 1.98 degrees with the successful recognition of the object by the frontal viewing camera(Heo et al., 2011). Conclusion: We made a new ergonomic interface system based on gaze tracking and object recognition Application: The proposed system can be used for helping the handicapped in home environment.

• Journal of the Ergonomics Society of Korea
• /
• v.34 no.5
• /
• pp.541-548
• /
• 2015

Objective: We introduce a hand gesture segmentation method using a wrist-worn wearable device which can recognize simple gestures of clenching and unclenching ones' fist. Background: There are many types of smart watches and fitness bands in the markets. And most of them already adopt a gesture interaction to provide ease of use. However, there are many cases in which the malfunction is difficult to distinguish between the user's gesture commands and user's daily life motion. It is needed to develop a simple and clear gesture segmentation method to improve the gesture interaction performance. Method: At first, we defined the gestures of making a fist (start of gesture command) and opening one's fist (end of gesture command) as segmentation gestures to distinguish a gesture. The gestures of clenching and unclenching one's fist are simple and intuitive. And we also designed a single gesture consisting of a set of making a fist, a command gesture, and opening one's fist in order. To detect segmentation gestures at the bottom of the wrist, we used a wrist strap on which an array of infrared sensors (emitters and receivers) were mounted. When a user takes gestures of making a fist and opening one's a fist, this changes the shape of the bottom of the wrist, and simultaneously changes the reflected amount of the infrared light detected by the receiver sensor. Results: An experiment was conducted in order to evaluate gesture segmentation performance. 12 participants took part in the experiment: 10 males, and 2 females with an average age of 38. The recognition rates of the segmentation gestures, clenching and unclenching one's fist, are 99.58% and 100%, respectively. Conclusion: Through the experiment, we have evaluated gesture segmentation performance and its usability. The experimental results show a potential for our suggested segmentation method in the future. Application: The results of this study can be used to develop guidelines to prevent injury in auto workers at mission assembly plants.

• Journal of Broadcast Engineering
• /
• v.23 no.2
• /
• pp.246-252
• /
• 2018

Hand gestures are attracting attention as a NUI (Natural User Interface) of wearable devices such as smart glasses. Recently, to support efficient media consumption in IoT (Internet of Things) and wearable environments, the standardization of IoMT (Internet of Media Things) is in the progress in MPEG. In IoMT, it is assumed that hand gesture detection and recognition are performed on a separate device, and thus provides an interoperable interface between these modules. Meanwhile, deep learning based hand gesture recognition techniques have been recently actively studied to improve the recognition performance. In this paper, we propose a method of hand gesture recognition based on CNN (Convolutional Neural Network) for various applications such as media consumption in wearable devices which is one of the use cases of IoMT. The proposed method detects hand contour from stereo images acquisitioned by smart glasses using depth information and color information, constructs data sets to learn CNN, and then recognizes gestures from input hand contour images. Experimental results show that the proposed method achieves the average 95% hand gesture recognition rate.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.11 no.1
• /
• pp.114-120
• /
• 2018

In this paper we implemented an EMG sensor system for wearable devices to obtain and analyze of EMG signals. The performance of the implemented sensor system is evaluated by the correlation analysis of muscle fatigue and muscle activation to clinical EMG system and compared with power consumption of the measured power of our system and commercial systems. In experiments with biceps and triceps brachii of 5 objects, The correlation values of muscle fatigue and muscle activation between our system and the clinical EMG system is 1.1~1.4 and about 1.0, respectively. And also the power consumption of our system is 25~50% less than that of some commercial EMG sensor systems.

• The Journal of the Korea Contents Association
• /
• v.15 no.3
• /
• pp.11-20
• /
• 2015

Recently, with the market of smart phones slowing down, more attention is paid to wearable devices. It was suggested that 2013 was the "year of the smart watch", due to that the majority of major consumer electronics manufacturers were undertaking work on a smart watch device. However there are still many issues on the interaction and interface design of smart watches. This study reviewed related literatures and evaluated the interaction methods, interface and content design of current smart watches. Based on that, future research directions were proposed. The research results have significant meanings for the guidance of future directions of smart watch.

• Journal of Communications and Networks
• /
• v.16 no.4
• /
• pp.465-474
• /
• 2014

Wireless sensor network (WSN) is considered to be one of the most important research fields for ubiquitous healthcare (u-healthcare) applications. Healthcare systems combined with WSNs have only been introduced by several pioneering researchers. However, most researchers collect physiological data from medical nodes located at static locations and transmit them within a limited communication range between a base station and the medical nodes. In these healthcare systems, the network link can be easily broken owing to the movement of the object nodes. To overcome this issue, in this study, the fast link exchange minimum cost forwarding (FLE-MCF) routing protocol is proposed. This protocol allows real-time multi-hop communication in a healthcare system based on WSN. The protocol is designed for a multi-hop sensor network to rapidly restore the network link when it is broken. The performance of the proposed FLE-MCF protocol is compared with that of a modified minimum cost forwarding (MMCF) protocol. The FLE-MCF protocol shows a good packet delivery rate from/to a fast moving object in a WSN. The designed wearable platform utilizes an adaptive linear prediction filter to reduce the motion artifacts in the original electrocardiogram (ECG) signal. Two filter algorithms used for baseline drift removal are evaluated to check whether real-time execution is possible on our wearable platform. The experiment results shows that the ECG signal filtered by adaptive linear prediction filter recovers from the distorted ECG signal efficiently.

• ETRI Journal
• /
• v.38 no.1
• /
• pp.149-158
• /
• 2016

In the field of augmented reality technologies, commercial optical see-through-type wearable displays have difficulty providing immersive visual experiences, because users perceive different depths between virtual views on display surfaces and see-through views to the real world. Many cases of augmented reality applications have adopted eyeglasses-type displays (EGDs) for visualizing simple 2D information, or video see-through-type displays for minimizing virtual- and real-scene mismatch errors. In this paper, we introduce an innovative optical see-through-type wearable display hardware, called an EGD. In contrast to common head-mounted displays, which are intended for a wide field of view, our EGD provides more comfortable visual feedback at close range. Users of an EGD device can accurately manipulate close-range virtual objects and expand their view to distant real environments. To verify the feasibility of the EGD technology, subject-based experiments and analysis are performed. The analysis results and EGD-related application examples show that EGD is useful for visually expanding immersive 3D augmented environments consisting of multiple displays.