• Investigative Magnetic Resonance Imaging
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• v.25 no.4
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• pp.229-251
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• 2021

Arteriosclerosis is the leading cause of stroke, with a fatality rate surpassing that of ischemic heart disease. High-resolution vessel wall magnetic resonance imaging is generally recognized as a non-invasive and panoramic method for the evaluation of arterial plaque; however, this method requires improved signal-to-noise ratio and scanning speed. Recent advances in high-density head and neck coil arrays are characterized by broad coverage, multiple channels, and closefitting designs. This review analyzes fast magnetic resonance imaging from the perspective of accelerated algorithms for vessel wall imaging and demonstrates the need for effective algorithms for signal acquisition using advanced radiofrequency system. We summarize different phased-array structures under various experimental objectives and equipment conditions, introduce current research results, and propose prospective research studies in the future.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.660-662
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• 2022

Due to the prolonged aftermath of COVID-19, the number of modern people suffering from stress and mental illness is increasing. Recently, various methods of color therapy are being studied using LED lighting to improve concentration, relieve stress, manage skin, and improve sleep quality. In this paper, pulse waves are measured and heart rate variability is extracted using a PPG (Photoplethysmogram) sensor to analyze a person's mental and physical state. Using RGBLED and Arduino, we propose a mood lighting system that automatically changes colors according to changes in mental and physical conditions by producing color lighting of various wavelengths, which are mainly used to stabilize the mental state.

• The Journal of Korean Medicine
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• v.33 no.1
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• pp.68-78
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• 2012

Objectives: The purpose of this study was to analyze the relationship between Yin-deficiency questionnaire score and various biofunctional signals in women. Methods: A retrospective chart review was performed on charts of 195 patients who visited Gangdong Kyung Hee Hospital between April 1st and September 30th, 2011. The subjects were categorized into two groups, a low Yin-deficiency group (n=118) and a high Yin-deficiency group (n=77). The authors analyzed the correlation between Yin-deficiency questionnaire score and biofunctional signals by Pearson's correlation coefficient test and the difference in biofunctional signals between the two groups by independent samples t-test using SPSS for windows. Results: 1. Negative correlations were observed between the temperature difference of back-humerus, standard deviation of all R-R intervals (SDNN), total power (TP), low frequency (LF), high frequency (HF) on heart rate variability parameters, and Yin-deficiency questionnaire score. A positive correlation was observed between the temperature difference of knee-humerus and Yin-deficiency questionnaire score. 2. The temperature difference of back-humerus in the high Yin-deficiency group was significantly higher than that in the low Yin-deficiency group. The temperature difference of knee-humerus, height, waist-hip ratio, SDNN, TP, LF, and HF of the high Yin-deficiency group were significantly lower than those of the low Yin-deficiency group. Conclusions: The results of this study suggest that the comprehensive diagnosis of Yin-deficiency and biofunctional signals is useful.

• CELLMED
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• v.5 no.1
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• pp.5.1-5.5
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• 2015

In this first double-blind-placebo-controlled investigation of the Aeon Patch, electrocardiographic data were acquired from 50 well-hydrated volunteers [21 females and 29 males, age: 19-79, weight: 117-334 lbs, height: 5'-6',3"], under 3 different conditions for a total duration of 15 min (5 min/condition). Condition1: Control (C) - while wearing no Patch, Condition 2: Placebo (P) or Active (A) - after wearing either the Placebo or the Aeon Patch for 20 min, and Condition 3: Active (A) or Placebo (P) - after wearing either the Aeon or the Placebo Patch for 20 min. There was a washout period of 15 min between Conditions 2 and 3. All involved in the investigation were blind to the (A) and (P) Patches as they looked exactly the same and were assigned in a random fashion. The hypothesis to be tested was: Wearing the Aeon Patch for 20 min reduces stress. Data were first quality assured and those subjects who showed a parasympathetic response after wearing the Patch within 20 min were identified as early responders. Thirty subjects (60%) achieved a relaxed state after wearing the Aeon Patch as early as 20 min. Statistical analysis (one-sample inference) was used to compare the spectral features of the responders. The normalized LF/HF decreased significantly ($24%{\pm}9%$ after 20 min) in condition (A) compared to condition (P) with a p-value < 0.047 (n = 30) in responders. Therefore, the hypothesis that wearing the Aeon Patch for 20 min reduces stress was accepted as true.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.3
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• pp.347-358
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• 2016

The paper presents a software architecture for a wearable device to measure vital signs with the real-time user's behavior recognition. Taking vital signs with a wearable device help user measuring health state related to their behavior because a wearable device is worn in daily life. Especially, when the user is running or sleeping, oxygen saturation and heart rate are used to diagnose a respiratory problems. However, in measuring vital signs, continuosly measuring like the conventional method is not reasonable because motion artifact could decrease the accuracy of vital signs. And in order to fix the distortion, a complex algorithm is not appropriate because of the limited resources of the wearable device. In this paper, we proposed the software architecture for wearable device using a simple filter and the acceleration sensor to recognize the user's behavior and measure accurate vital signs with the behavior state.

• Journal of Digital Contents Society
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• v.19 no.1
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• pp.103-112
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• 2018

In this paper, we propose a method of recognizing emotions using PPG sensor which measures blood flow according to emotion. From the existing PPG signal, we use a method of determining positive emotions and negative emotions in the frequency domain through PSD (Power Spectrum Density). Based on James R. Russell's two-dimensional prototype model, we classify emotions as joy, sadness, irritability, and calmness and examine their association with the magnitude of energy in the frequency domain. It is significant that this study used the same PPG sensor used in wearable devices to measure the top four kinds of emotions in the frequency domain through image experiments. Through the questionnaire, the accuracy, the immersion level according to the individual, the emotional change, and the biofeedback for the image were collected. The proposed method is expected to be various development such as commercial application service using PPG and mobile application prediction service by merging with context information of existing smart phone.

• Journal of Digital Policy
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• v.1 no.2
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• pp.61-69
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• 2022

The paper is a study to develop and verify a blood glucose level prediction model based on biosignals obtained from photoplethysmography (PPG) sensors, ICT technology and data. Blood glucose prediction used the MLP architecture of machine learning. The input layer of the machine learning model consists of 10 input nodes and 5 hidden layers: heart rate, heart rate variability, age, gender, VLF, LF, HF, SDNN, RMSSD, and PNN50. The results of the predictive model are MSE=0.0724, MAE=1.1022 and RMSE=1.0285, and the coefficient of determination (R²) is 0.9985. A blood glucose prediction model using bio-signal data collected from digital devices and machine learning was established and verified. If research to standardize and increase accuracy of machine learning datasets for various digital devices continues, it could be an alternative method for individual blood glucose management.

• Journal of the Ergonomics Society of Korea
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• v.25 no.4
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• pp.129-135
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• 2006

he purpose of this study is to measure bio-signal to investigate the driver's physiological response change under real situation using train simulator. The train simulator used in this study is KTX model and according to changes of driving situation, The bio-signal controlled by autonomic nervous system, such as GSR(Galvanic Skin Response), SpO2(Saturation percent O2), HR(Heart Rate), ECG(Electrocardiograph), EEG(Electroencephagram) and movement and response of eye were measured. Statistically significant difference in bio-signal data and eye movement activity pattern were investigated under several different driving speeds using analysis of variance (p<0.05). The GSR and HR value measured in average and mission speed operation is higher than in high-speed operation. β wave of EEG in average speed operation become more activated than in high speed operation. In accordance with a characteristic of rail vehicle, movement and response of eye in high-speed operation requiring relatively simple maneuver become less activated than in either average or mission speed operations. Conclusively, due to more careful driving controls in average and mission speed operation are required than in high-speed operation, level of mental and physical stresses of train driver was increased and observed through changes of bio-signal and eye movement measured in this study.

• The Korean Journal of Pharmacology
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• v.31 no.3
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• pp.279-284
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• 1995

The aim of the present study was to know whether exogenously administered nitric oxide (NO) may differently modulate muscle mechanics between heart and aorta. We used PIANO method to generate NO. In isolated rat atrial tissues, neither heart rate nor contractility was affected by PIANO $(STZ,\;30{\sim}100\;{\mu}M)$. Only high concentration $(100\;{\mu}M)$ of 8-bromo cyclic GMP slightly depressed cardiac contractility. However, the same concentrations of 8-Br cGMP and PIANO significantly relaxed the rat thoracic aorta contracted with phenylephrine $(0.1\;{\mu}M)$. In isolated rabbit cardiac atrial myocytes, the amplitude of calcium currents were decreased in the whole voltage range by the presence of streptozotocin, which was further potentiated by UV light. Calcium currents were also decreased in those preparations treated with bradykinin, nitroprusside and 8-Br cGMP. These findings suggest that exogenous NO may modulate calcium current in cardiac myocyte. However, it remains why this does not affect myocardial contractility and heart rate. We concluded that NO may differently regulate calcium signal between aorta and heart muscle.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.328-330
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• 2004

In this paper, ECG based cardiac disease diagnosis models are developed. Conventionally, ECG monitoring equipments can only measure and store ECG signals and they always require medical doctor's diagnosis actions which are not desirable for continuous ambulatory monitoring and diagnosis healthcare systems. In this paper, two kinds of neural based self cardiac disease diagnosis engines are developed and tested for four kinds of diseases, sinus bradycardia, sinus tachycardia, left bundle branch block and right bundle branch block. For diagnosis engines, error backpropagation neural network (BP) and probabilistic neural network (PNN) were applied. Five signal features including heart rate, QRS interval, PR interval, QT interval, and T wave types were selected for diagnosis characteristics. To show the validity of proposed diagnosis engine, MIT-BIH database were used to test. Test results showed that BP based diagnosis engine has 71% of diagnosis accuracy which is superior to accuracy of PNN based diagnosis engine. However, PNN based diagnosis engine showed superior diagnosis accuracy for complex-disease diagnoses than BP based diagnosis engine.