• Journal of Advanced Navigation Technology
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• v.24 no.4
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• pp.322-327
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• 2020

Recently, a research on obtaining a vital signal using a Doppler radar has been developed and is used as a technology applied to patients in bed. However, in the case of the measured pulse, the respiration signal is generated as noise, resulting in a problem of lowering accuracy. In this paper, we propose a bio-signal measurement algorithm based on the sampling point to improve the accuracy of the signal for measuring the pulse rate when measuring bio-signals using a Doppler radar. The proposed algorithm improves the accuracy of the measured bio-signal by removing noise generated when measuring biosignals based on two sampling points. Compared with actual medical equipment and existing bio-signal algorithms, it is more than 90% similar to medical equipment. In addition, it was confirmed that severe amplitude change was minimized compared to the existing algorithm.

• Journal of Biomedical Engineering Research
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• v.19 no.3
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• pp.261-268
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• 1998

Electrogastrography(EGG), the cutaneous recording of the myoelectrical activity of the stomach using surface electrodes, is a non-invasive technique to detect gastric motility disorder, We developed a detection and analysis system for the EGG signal, which consists of hardware(bio-amplifier, filter) and softwere(user interface, analysis algorithm, patient database). The EGG signal was amplified and filtered by 3 channel bio-amplifiers, and simultaneously digitized and stored on IBM PC with a sampling frequency of 16 Hz. The stored EGG signal was analyzed using developed algorithm to extract clinically useful information from the signal. The developed system has tested through animal experiments, and is under clinical evaluation.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.1
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• pp.43-49
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• 2023

In modern wireless communication systems including beamformers or location-based services (LBS), which employ multiple antenna elements, estimating the number of signals is essential for accurately determining the quality of the communication service. Representative signal number estimation algorithms including the Akaike information criterion (AIC) and minimum description length (MDL) algorithms, which are information theoretical criterion models, determine the number of signals based on a reference value that minimizes each criterion. In general, increasing the number of elements mounted onto the array antenna enhances the performance of estimating the number of signals; however, it increases the computational complexity of the estimation algorithm. In addition, various configurations of array antennas for the increased number of antenna elements should be considered to efficiently utilize them in a limited location. In this paper, we introduce an efficient signal number estimation algorithm based on the beamspace based AIC and MDL techniques that reduce the computational complexity by reducing the dimension of a uniform circular array antenna. Since this algorithm is based on a uniform circular array antenna, it presents the advantages of a circular array antenna. The performance of the proposed signal number estimation algorithm is evaluated through computer simulation examples.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.238-240
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• 2018

Recently, healthcare services have been developed and studied using various bio-signal analysis tools. Most bio-signal analysis studies utilize Matlab and R Programming. However, in order to apply the algorithm developed by Matlab and R Programming to the system, it is necessary to convert the source code. This paper proposes a smart interface that can skip source code conversion.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.65-67
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• 2017

Due to the development of mobile computing and wearable technology, various wearable devices for measuring bio-signals in everyday life have been developed and popularized, and healthcare services utilizing bio-signals are attracting attention. In recent years, healthcare services have been developed and studied using various bio-signal analysis tools. Most bio-signal analysis studies utilize Matlab. However, in order to apply the algorithm developed in Matlab to the system, it is necessary to convert the source. We want to provide a smart interface that can skip source conversion. In this paper, we develop an interface to run the source file itself in the system by omitting the conversion technique for applying the algorithm developed in Matlab to the system.

• Journal of information and communication convergence engineering
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• v.18 no.2
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• pp.132-146
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• 2020

Biometric technologies have become widely available in many different fields. However, biometric technologies using existing physical features such as fingerprints, facial features, irises, and veins must consider forgery and alterations targeting them through fraudulent physical characteristics such as fake fingerprints. Thus, a trend toward next-generation biometric technologies using behavioral biometrics of a living person, such as bio-signals and walking characteristics, has emerged. Accordingly, in this study, we developed a bio-signal authentication algorithm using electrocardiogram (ECG) signals, which are the most uniquely identifiable form of bio-signal available. When using ECG signals with our system, the personal identification and authentication accuracy are approximately 90% during a state of rest. When using fingerprints alone, the equal error rate (EER) is 0.243%; however, when fusing the scores of both the ECG signal and fingerprints, the EER decreases to 0.113% on average. In addition, as a function of detecting a presentation attack on a mobile phone, a method for rejecting a transaction when a fake fingerprint is applied was successfully implemented.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.3
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• pp.333-333
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• 2023

• Journal of Internet of Things and Convergence
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• v.7 no.4
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• pp.1-7
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• 2021

Recently, technological differentiation(sensor, AI) of products using IoT technology to satisfy consumer needs in the mature market for smart home appliances has received a lot of positive responses. However, air conditioner products are in the early stages of convergence technology. Therefore, air conditioner products are fields that require ICT technologies for information production, collection, processing, storage, and service development beyond IoT. In this paper, we collect and store contactless bio-signal using IR-UWB radar technology. The blowing direction of the air conditioning is controlled according to bio-signal and user's sleep is monitored to provide an optimal sleep environment. In addition, we propose a service algorithm that can provide comfort with changes in the optimal conditions of air conditioning and emotional lighting depending on the discomfort index environment. Through this study, we developed an intelligent smart air conditioning service platform with ICT technology of bio-signal, discomfort index, and emotional lighting.

• Journal of IKEEE
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• v.12 no.2
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• pp.87-94
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• 2008

Pelvic floor muscle is the main subsystem that maintains urinary continence. It is possible to diagnose the degree of the stress urinary incontinence(SUI) by evaluating the contraction pressure of the pelvic floor muscle. Bio-signal measurement system was developed to measure the contraction pressure. Diagnostic parameters were drawn out by analyzing the measured data. Statistical evaluations were done to classify the all subjects with five groups each has similar characteristics. SUI diagnostic algorithm was implemented to each group separately. The accuracy of the algorithm was about 78.9% and utility was confirmed by clinical trial.