• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.4
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• pp.97-104
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• 2010

In this paper, we provide an embedded type non-contact bio-radar heart and respiration rate monitoring system. We implemented the rate finding algorithm into the embedded system. The high-speed and reliable real-time signal processor is then tested. To avoid null-point data loss problem, we applied quadrature demodulation. Among several other combining techniques, we suggest arctangent demodulation for quadrature channel combining and DSP is used for real-time signal processing. We also suggest DC-offset compensation technique to preserve the wanted DC components of the IQ signals for accurate demodulation while keeping the dynamic range of the ADC lower. Using Texas Instrument C6711 series DSP and external 12Bit ADC, we implemented proper elliptic digital filter and autocorrelation detection algorithm for robust commercial hand held device.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.9
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• pp.379-385
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• 2012

This paper suggests U-healthcare system for individual health management realizing the gateway, client, and Java-based network server by using the vital signal measuring system and android-based mobile platform. This study realized the vital signal measuring system based on the technology to measure the ECG, oxygen saturation, blood pressure, and respiration, etc. And all the information of measurement was transmitted to the mobile gateway using the 3-bite transmission protocol consisting of headers and data. The data transmitted to the mobile gateway was used to examine the mobile client's personal health indexes through the network server. This paper realized and tested the android-based gateway, client, and the broadcasting network server and verified their validity with simulations and actual humans. As a result, the U-healthcare system suggested was proved to be effective in managing each individual's health from short distance and long distance. And it could examine each individual's health conditions in real-time and was found to be advantageous in that it could secure the guardian's mobility.

• Journal of Digital Contents Society
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• v.18 no.1
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• pp.87-91
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• 2017

Recently, several kinds of researches using IoT wearable devices are active in the field of sports, design, emotional sciences and so on. The human bio data such as blood pulse, ECG, SKT signal, and GSR Signal producing from IoT wearable devices such as Watch, Smart-band, Grass can adapt to the meaningful future applications. Using the human's emotional data and a physical status with variation and so on, we can individually get the personal status. Due to knowing the personal emotion or physical status is related and connected to the valuable wallet of customers, the approach is more important in nowadays. Therefore, the personal information can effectively adapt to the marketing of the culture industry, which deals with emotions of customers. The research shows implementation steps for explaining overall architecture of the convergence research between Art and Technologies.

• The Journal of the Convergence on Culture Technology
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• v.6 no.3
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• pp.427-430
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• 2020

The multi-channel analog signal to digital signal conversion is increasing in the field of IoT and medical measurement equipments. It has chip area and power consumption constraints to use a few single or 2_channel ADC for multi_channel application. This paper described to design and implement a proposed comb filter for multi-channel, 24bit ADC. The function of proposed comb filter is verified by matlab simulation and the FPGA test board. It was fabricated using SK Hynix 0.35㎛ CMOS standard process. The performance and chip size is compared with the existing design method that uses integrator/differentiator and FIR construction. The proposed comb filter is expected to use the IoT product and medical measurement equipments that require multi-channel, low power consumption and small hardware size.

• Journal of Sensor Science and Technology
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• v.5 no.1
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• pp.43-50
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• 1996

This paper presents a manufacture of the multiple subjects biotelemetry system using custom CMOS IC fabricated $1.5{\mu}m$ n-well process technology. The implantable circuits of the system except sensor interface circuits including FM transmitter are fabricated on a single chip with the sire of $4{\times}4mm^{2}$. It is possible to assemble the implantable system in a hybrid package as small as $3{\times}3{\times}2.5cm$ by using this chip, It's main function is to enable continuous measurement simultaneously up to 7-channel physiological signals from the selected one among 8 subjects. Another features of this system are to enable continuous measurement of physiological signals, and to accomplish ON/OFF switching of an implanted battery by subject selection signal with command signal from the external circuit. If this system is coupled with another appropriate sensors in medical field, various physiological parameters such as pressure, pH and temperature are to be measured effectively in the near future.

• Journal of the Institute of Convergence Signal Processing
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• v.1 no.1
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• pp.15-22
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• 2000

The analysis of power spectrum based on linear AR model is applied widely to quantize the response of autonomic nerve noninvasively, In this paper, we estimate the power spectrum density for heartrate variability of the electrocadiogram and pulse wave for short term data(less than two minute), The time series of heart rate variability is obtained from the time interval(RRI, PPI) between the feature point of the electrocadiogram and pulse wave for normal person, The generated time series reconstructed into new time series through polynomial interpolation to apply to the AR mode. The power spectrum density for AR model is calculated by Burg algorithm, After applying AR model, the power spectrum density for heart rate variability of the electrocadiogram and the pulse wave is shown smooth spectrum power at the region of low frequence and high frequence, and that the power spectrum density of electrocadiogram and pulse wave has similar form for same subject.

• Journal of Biomedical Engineering Research
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• v.24 no.3
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• pp.151-158
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• 2003

Numerous studies of short-term, beat-to-beat variability in cardiovascular signals have used linear analysis techniques. However, no study has been done about the appropriateness of linear techniques or the comparison between linearities and nonlinearities in short-term, beat-to-beat variability. This paper aims to verify the appropriateness of linear techniques by investigating nonlinearities in short-term, beat-to-beat variability. We compared linear autoregressive moving average(ARMA) with nonlinear neural network(NN) models for predicting current instantaneous heart rate(HR) and mean arterial blood pressure(BP) from past HRs and BPs. To evaluate these models. we used HR and BP time series from the MIMIC database. Experimental results indicate that NN-based nonlinearities do not play a significant role and suggest that 10 technique provides adequate characterization of the system dynamics responsible for generating short-term, beat-to-beat variability.

• Journal of Biomedical Engineering Research
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• v.40 no.1
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• pp.32-37
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• 2019

In this study, we designed a blending algorithm for rate adaptive pacing for cardiac pacemaker. Generally, rate adaptive pacing (RAP) is applied to patients whose heart rate does not rise during exercise for chronotropic incompetence (CI) patient. It is very important to develop an algorithm for RAP that can be properly applied to CI patients. In order to design an RAP algorithm we used dual sensors. Firstly, we designed a bio-signal measurement system based on the dual sensors, which are accelerometer and respiratory system. Secondly, we conducted treadmill test for the simulation experiment while using 3-lead ECG as reference. Finally, we designed a blending algorithm based on activation state of the dual sensors. The proposed blending algorithm was subdivided into three sections based on the accelerometer signal, which are rapidly increased section (W1), hardly changed section (W2), and decreased section (W3). Each weight is set aside for each section. To evaluate this algorithm, ten healthy adult males were participated. The correlation and Root Mean Square Error between the proposed algorithm and the reference were compared, and shown to be r=0.88 and 2.82 bpm, respectively. These results show that the proposed blending algorithm of dual sensors enables proper tracking of the heart rate during exercise. Also, it shows the possibility that the proposed blending algorithm can be applied to improve quality of life of the chronotropic incompetence patient.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.36 no.5
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• pp.83-91
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• 2020

Environmental conditions are known to impact human health and behavior, emotions such as pleasure, anxiety, and depression, and reduce stress. Interior design that elevates emotional comfort and satisfaction can help improve mental health and well-being. This study is a systematic review that analyzed previous empirical studies that explored the effect of interior design elements on the user's emotional response which is quantitatively evaluated by bio-signal and qualitatively evaluated through self-reported questionnaire surveys. This paper aims to derive the attributes of interior design and biometric indicators that affect the user's positive emotion through the synthesis of previous studies and to confirm the feasibility of measuring bio-signals as an objective evaluation tool for architectural design and as a quantitative research method. As a result of the review, the biometric data from EEG, fMRI, ECG, EMG, GSR, and eye-tracking were used to measure the participants' emotional responses, which were manifested as positive or negative depending on certain attributes of interior design such as the form, color, lighting, material and furniture. The attributes of interior design related to the positive emotional response were the curved shape, high ceiling, openness of space, and subdued tone colors. Standard lighting conditions and wooden spaces were related to stress reduction in terms of comfort and relaxation. The free arrangement of furniture was related to the user's positive emotions. On the other hand, consistent experimental protocols could not be found, and although the sample sizes of the studies were small, the studies have demonstrated the feasibility of the emotional response measurement by using the biometric data. Therefore this method can be a useful objective tool in the measurement of human-centric data in architectural design, and to develop the evidence-based design to induce positive emotions and minimize stress.

• Fashion & Textile Research Journal
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• v.24 no.6
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• pp.694-706
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• 2022

This study focusses on the development of a motion-sensing smart leggings prototype with the help of a module that monitors motion using a fiber-type stretch sensor. Additionally, it acquires data on Electrocardiogram (ECG), respiration, and body temperature signals, for the development of smart clothing used in online exercise coaching and customized healthcare systems. The research process was conducted in the following order: 1) Fabrication of a fiber-type elastic strain sensor for motion monitoring, 2) Positioning and attaching the sensor, 3) Pattern development and three-dimensional (3D) design, 4) Prototyping 5) Wearability test, and 6) Expert evaluation. The 3D design method was used to develop an aesthetic design, and for sensing accurate signal acquisition functions, wearability tests, and expert evaluation. As a result, first, the selection or manufacturing of an appropriate sensor for the function is of utmost importance. Second, the selection and attachment method of a location that can maximize the function of the sensor without interfering with any activity should be studied. Third, the signal line selection and connection method should be considered, and fourth, the aesthetic design should be reflected along with functional verification. In addition, the selection of an appropriate material is important, and tests for washability and durability must be made. This study presented a manufacturing method to improve the functionality and design of smart clothing, through the process of developing a prototype of motion-sensing smart leggings.