• Journal of the Korean Electrochemical Society
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• v.25 no.4
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• pp.125-133
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• 2022

Along with the increasing need for point-of-care diagnostics, development of portable, user-friendly, as well as sensitive sensors have gained intensive attention. Among various strategies, electrochromic sensors, which are electrochemically operated colorimetric sensors, have been actively studied. With their ability to report the presence and concentration of analytes by optical signals, electrochromic sensors utilize the advantages of both electrochemical and colorimetric sensors, enabling the simplification of device composition as well as convenient interpretation of results. Up to date, electrochromic sensors have been applied for a wide range of analytes, and further developments such as the introduction of flexible platforms or self-powered systems have been reported, providing a path towards the development of wearable sensor devices. In this review, various types of electrochromic sensors, according to the main strategy in which the electrochemical signals are converted to colorimetric signals, are introduced.

• Journal of the Korean Electrochemical Society
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• v.21 no.4
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• pp.80-87
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• 2018

Safety issues in Li-ion battery system have been prime concerns, as demands for power supply device applicable to wearable device, electrical vehicles and energy storage system have increased. To solve safety problems, promising strategy is to replace organic liquid electrolyte with non-flammable solid electrolyte, leading to the development of all-solid-state battery. However, relative low conductivity and high resistance from rigid solid-solid interface hinder a wide application of solid electrolyte. Composite electrolytes composed of organic and inorganic parts could be alternative solution, which in turn bring about the increase of conductivity and conformal contact at physically rough interfaces. In our study, composite electrolytes were prepared by combining poly(ethylene oxide)(PEO) and $Li_7La_3Zr_2O_{12}$ (LLZO). The crystallinity, morphology and electrochemical performances were investigated with the control of LLZO contents from 0 wt% to 50 wt%. From the results, it is concluded that optimum content and uniform dispersion of LLZO in polymer matrix are significant to improve overall conductivity of composite electrolyte.

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

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.12
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• pp.1106-1113
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• 2013

For patients who have senile mental disorder such as dementia, quantity of excercise and amount of sunlight are important clue for dose and the treatment. Therefore, monitoring health information of daily life is necessary for patients' safety and healthy life. Portable & wearable sensor device and server configuration monitoring data are needed to provide these services for patients. Watch-type device(smart watch) which patients wear and server system are developed in this paper. Smart watch developed includes GPS, accelerometer and illumination sensor, and can obtain real time health information by measuring the position of patients, quantity of exercise and amount of sunlight. Server system includes the sensor data analysis algorithm and web server that doctor and protector can monitor through sensor data acquired from smart watch. The proposed data analysis algorithm acquires quantity of exercise information and detects step count in patients' motion acquired from acceleration sensor and to verify this, the three cases with fast pace, slow pace, and walking pace show 96% of the experimental result. If developed u-Healthcare System for dementia patients is applied, more high-quality medical service can be provided to patients.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.1
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• pp.220-226
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• 2011

Device of the ECG and pulse signal was made to measure PTT signal using non-invasive method and possible to wearable. PTT alterations were observed according to position change using implemented system.It was needed to ECG and pulse to detect the PTT, used the photoplethymorgraphy appeared to change the blood volume. And also wireless sensor node which was able to Zigbee compatibility was used to transfer the detected ECG and pulse signal to PC. Noise was removed from transit data and algorithm was applied to calculate the PTT. After the evaluation of both the conventional measuring systems and the proposed photoplethymography measuring system, a highly effective and efficient formation and distribution sequences were found within the proposed photoplethymography measuring system.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.3
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• pp.176-181
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• 2016

In this paper, the autonomous mobile robot control system for detecting fire was proposed using the wearable device based on EMG(Electromyogram) signal. Myo armband is used for detecting the user's EMG signal. The gesture was classified after sending the data of EMG signal to a computer using Bluetooth communication. Then the robot named 'uBrain' was implemented to move by received data from Bluetooth communication in our experiment. 'Move front', 'Turn right', 'Turn left', and 'Stop' are controllable commands for the robot. And if the robot cannot receive the Bluetooth signal from a user or if a user wants to change manual mode to autonomous mode, the robot was implemented to be in the autonomous mode. The robot flashes the LED when IR sensor detects the fire during moving.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.2
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• pp.127-137
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• 2011

We have developed a wearable device that can convert sensor data into real-time step counts and activity levels. Sensor data on gait were acquired using a triaxial accelerometer. A test was performed according to a test protocol for different walking speeds, e.g., slow walking, walking, fast walking, slow running, running, and fast running. Each test was carried out for 36 min on a treadmill with the participant wearing a portable gas analyzer (K4B2), an Actical device, and the device developed in this study. The signal vector magnitude (SVM) was used to process the X, Y, and Z values output by the triaxial accelerometer into one representative value. In addition, for accurate step-count detection, we used three algorithms: an heuristic algorithm (HA), the adaptive threshold algorithm (ATA), and the adaptive locking period algorithm (ALPA). A regression equation estimating the energy expenditure (EE) was derived by using data from the accelerometer and information on the participants. The recognition rate of our algorithm was 97.34%, and the performance of the activity conversion algorithm was better than that of the Actical device by 1.61%.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.13-18
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• 2008

In these days, wearable and mobile physiological sensing devices have been studied according to the increasing interest on the healthy and wellbeing life. However, these sensing devices display just the sensing results, such as heart rate, skin temperature, and its daily records. In this work, we propose the novel type of mobile physiological sensing device which deliver the user comfortable grabbing feeling. In addition, we indicate the personalized physiological signal analysis result which be concluded by the different analysis results according to the person to person. In order to verify this sensing device, we collect the data set from 4 different users during a week and measure the physiological signal such as heart rate, hand temperature, and skin conductance. And we observe the result how the analysis results shows the difference between the users. We expect that this work can be applied in the various health care applications in the near future.

• The KIPS Transactions:PartD
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• v.18D no.2
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• pp.143-148
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• 2011

In this paper developed a wearable activity device and algorithm which can be converted into the real-time activity and monitoring by acquiring sensor row data to be occurred when a person is walking by using a tri-axial accelerometer. Test was proceeded at various step speeds such as slow walking, walking, fast walking, slow running, running and fast running, etc. for 36 minutes in accordance with the test protocol after wearing a metabolic test system(K4B2), Actical and the device developed in this study at the treadmill with 59 participants of subjects as its target. To measure the activity of human body, a regression equation estimating the Energy Expenditure(EE) was drawn by using data output from the accelerometer and information on subjects. As a result of experiment, the recognition rate of algorithm being proposed was shown the activity conversion algorithm was enhanced by 1.61% better than the performance of Actical.

• Journal of Biomedical Engineering Research
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• v.30 no.6
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• pp.503-509
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• 2009

The development of technology has led to ubiquitous health care service, which enables many patients to receive medical services anytime and anywhere. For the ubiquitous health care environment, real-time measurement of biomedical signals is very important, and the medical instruments must be small and portable or wearable. So, such devices have been developed to measure biomedical signals. In this study, we develop the biomedical monitoring device which is sensing the PPG signal, one of the useful signal in the field of ubiquitous healthcare. We design a watch-like biomedical signal monitoring system without a finger probe to prevent the user's inconvenience. This system obtains the PPG from the radial artery using a sensor in the wrist band. But, new device developed in this paper is easy to get the motion artifacts. So, we proposed new algorithm removing the motion artifacts from the PPG signal. The method detects motion artifacts by changing the degree of brightness of the light source. If the brightness of the light source is reduced, the PPG pulses will disappear. When the PPG pulses have disappeared completely, the remaining signal is not the signal that results from the changing blood flow. We believe that this signal is the motion artifact and call it the noise reference signal. The motion artifacts are removed by subtracting the noise reference signal from the input signal. We apply this algorithm to the system, so we can stabilize the biomedical monitoring system we designed.