• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1998년도 추계학술대회
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• pp.263-264
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• 1998

In this paper, we present the result of feature points recognition and classification of radial pulse by the shape of pulse wave. And we analyze radial pulse in frequency domain. The recognition algorithm use the method which runs in parallel with both the data of ECG and differential pulse simultaneously to recognize the feature points. Also fie specified 3-time elements of pulse wave as main parameters for diagnosis and measured them by execution of algorithm, then we classify the shape of radial pulse by existence and position of feature points. lastly we execute frequency analysis on the feature points and get the power spectrum of radial pulse.

• 대한한의진단학회지
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• 제9권2호
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• pp.57-71
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• 2005

Background and purpose: Maek Kyoung(脈經) is a book written, compiled, and edited by Wang Hui circa 3 A.D. This book is the first technical book devoted to the diagnostics. These are very important data but never make a special study and translate. so I hope this treatise can be great help to understand diagnosis study. Methods: Maek Kyoung(脈經) consists of ten volumes, and the third volume consists of the five chapters, including inter-generation and inter-restriction of the five viscera and the six entrails and prognosis of diseases. This treatise is made up of principal, notes, study and conclusion, we tried to make a translation faithful to the original. Results and Conclusion: Chapter 5 refers to three things. The first is relation between kidney and urinary bladder, the second is ordinary and extraordinary pulse condition of kidney, and the third is how to treat diseases related to kidney.

• International journal of advanced smart convergence
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• 제9권4호
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• pp.62-73
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• 2020

In this paper, we present electronic acupuncture needles we have developed using intelligence technology based on Bluetooth in order to allow anyone to simply receive customized remote diagnosis and treatment by clicking on the menu of the smartphone regardless of time and place. In order to determine the health condition and disease of patients, we have developed a software and a hardware of electronic acupuncture needles, operating on Bluetooth which transmits biometric data to oriental medical doctors using the functions of automatically determining pulse diagnosis, tongue diagnosis, and oxygen saturation; the functions are most commonly used in herbal treatment. In addition, using fuzzy logic and reasoning based on smartphones, we present in this paper an algorithm and the results of completion of hardware implementation for electronic acupuncture needles, appropriate for the body conditions of patients; the algorithm and the hardware implementation are for a treatment time duration by electronic acupuncture needles, an automatic determinations of pulse diagnosis, tongue diagnosis, and oxygen saturation, a function implementation for automatic display of acupuncture point, and a strength adjustment of electronic acupuncture needles. As a result of our simulation, we have shown that the treatment of patients, performed using an Electronic Acupuncture Needles based on intelligence, is more efficient compared to the treatment that was performed before.

• 한국콘텐츠학회논문지
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• 제9권10호
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• pp.249-257
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• 2009

사상의학은 체질에 따라 치료하는 방법을 달리하므로, 체질진단의 객관화가 절실히 요구되고 있다. 본 연구는 맥파를 이용하여 사상체질을 객관적으로 진단함에 있어서, 정확도가 높으면서 실용적인 체질분류 방법을 탐색하는 것이 목적이다. 한방병원에 건강검진을 목적으로 내원한 2848명의 피험자를 대상으로 전문의가 진단한 체질, 체질량지수, 혈압, 맥파 자료를 입수하였다. 자료의 선별과정을 통하여 최종적으로 1635명의 자료를 분석에 사용하였다. 판별분석, 회귀분석, 의사결정나무, 신경망으로 체질을 예측하고 전문의가 진단한 결과와 비교하여 분류방법의 정확도를 비교하였다. 판별분석은 체질별로 공분산 행렬이 동일해야 한다는 가정을 만족시키기 어려웠으며, 체질량지수를 고려하지 않은 의사결정나무와 신경망 분석의 결과는 분석표본의 변동에 민감했다. 체질분류에 결정적인 영향을 미치는 변수인 체질량지수가 고려된 로지스틱 회귀분석 또는 의사결정나무 방법이 체질분류 방법으로 추천할 만하다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권4호
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• pp.1209-1223
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• 2022

Blood pressure is one of the key physiological parameters for determining human health, and can prove whether human cardiovascular function is healthy or not. In general, what we call blood pressure refers to arterial blood pressure. Blood pressure fluctuates greatly and, due to the influence of various factors, even varies with each heartbeat. Therefore, achievement of continuous blood pressure measurement is particularly important for more accurate diagnosis. It is difficult to achieve long-term continuous blood pressure monitoring with traditional measurement methods due to the continuous wear of measuring instruments. On the other hand, radar technology is not easily affected by environmental factors and is capable of strong penetration. In this study, by using machine learning, tried to develop a linear blood pressure prediction model using data from a public database. The radar sensor evaluates the measured object, obtains the pulse waveform data, calculates the pulse transmission time, and obtains the blood pressure data through linear model regression analysis. Confirm its availability to facilitate follow-up research, such as integrating other sensors, collecting temperature, heartbeat, respiratory pulse and other data, and seeking medical treatment in time in case of abnormalities.

• 전기학회논문지
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• 제56권6호
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• pp.1092-1098
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• 2007

Since one decade, the detection of HFPD (High frequency Partial Discharge) has been proposed as one of the effective method for the diagnosis of the power component under service in power grids. As a tool for HFPD detection, Metal Foil sensor based on the embedded technology has been commercialized for mainly power cable due to its advantages. Recently, for the on-site noise discrimination, several PA (Pulse analysis) methods have been reported and the related software, such as Neural Network and Fuzzy, have been proposed to separate the PD (Partial Discharge) signals from the noises since their wave shapes are completely different from each other. On the other hand, the relevant fundamental investigation has not yet clearly made while it is reported that the effectiveness of the current methods based on PA is dependant on the types of sensors. Moreover, regarding the identification of the vital defects introducible into the Power Cable, the direct identification of the nature of defects from the PD signals through Metal Foil coupler has not yet been realized. As a trial for solving above shortcomings, different types of software have been proposed and employed without any convincing probability of identification. In this regards, our novel algorithm 'PA Map' based on the pulse analysis is suggested to identify directly the defects inside the power cable from the HFPD signals which is output of the HFCT and metal foil sensors. This method enables to discriminate the noise and then to make the data analysis related to the PD signals. For the purpose, the HFPD detection and PA (Pulse Analysis) system have been developed and then the effect of noise discrimination has been investigated by use of the artificial defects using real scale mockup. Throughout these works, our system is proved to be capable of separating the small void discharges among the very large noises such as big air corona and ground floating discharges at the on-site as well as of identifying the concerned defects.

• 대한한방부인과학회지
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• 제28권4호
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• pp.31-45
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• 2015

Objectives : The purpose of this study is to examine the relationship between the symptoms of primary dysmenorrhea and pulse energy of Chon, Gwan and Cheok. Methods The subjects of this study who had certain range of dysmenorrhea symptom. The degree of dysmenorrhea were assessed by Visual Analog Scale (VAS), Multidimensional Verbal Rating Scale (MVRS), Cox Menstrual Symptom Scale (CMSS) and measured by 3D Blood Pressure Pulse Analyzer(3D-MAC) tests at menstruation start date. Data analysis included descriptive statistics and multiple linear regression using the SPSS/WIN 18.0 program. Results : The induced results are as follows;The induced results are as follows 1. There were no significant relationship between the pulse energy and the sum values of VAS, MVRS and checking part of severity of CMSS. 2. The frequency domain of CMSS were significantly associated with pulse energy. 3. In linear regression models, the model of Left Chon had the especially highest value of explanatory power. (R ² = 0.517) Conclusions : The pulse energy changes are related to the symptoms of primary dysmenorrhea.

• 한국자기학회지
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• 제22권4호
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• pp.136-141
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• 2012

본 연구에서는 집게형 맥진기와 심전도계를 이용하여 전기적인 심전도 파형과 요골동맥파형을 동시 측정하여 얻은 맥파전달속도를 분석하였다. 두 신호의 동시 측정에 의한 맥파전달속도는 평균 6 m/s의 값을 보여 주었으며, ECG 파형과 홀소자 맥진파형으로 동시 측정한 방법은 기존 방법들 보다 정확하게 맥파전달속도를 측정할 수 있는 새로운 방법임을 입증하였다. 따라서 이결과는 한방의료기기인 맥진기에서 측정된 데이터를 임상적으로 활용할 수 있음을 보인다.

• 대한의용생체공학회:의공학회지
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• 제41권5호
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• pp.185-194
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• 2020

Arrhythmia is basically diagnosed with the electrocardiogram (ECG) signal, however, ECG is difficult to measure and it requires expert help in analyzing the signal. On the other hand, the radial pulse can be measured with easy and uncomplicated way in daily life, and could be suitable bio-signal for the recent untact paradigm and extensible signal for diagnosis of Korean medicine based on pulse pattern. In this study, we developed an irregular radial pulse detection algorithm based on a learning model and considered its applicability as arrhythmia screening. A total of 1432 pulse waves including irregular pulse data were used in the experiment. Three data sets were prepared with minimal preprocessing to avoid the heuristic feature extraction. As classification algorithms, elastic net logistic regression, random forest, and extreme gradient boosting were applied to each data set and the irregular pulse detection performances were estimated using area under the receiver operating characteristic curve based on a 10-fold cross-validation. The extreme gradient boosting method showed the superior performance than others and found that the classification accuracy reached 99.7%. The results confirmed that the proposed algorithm could be used for arrhythmia screening. To make a fusion technology integrating western and Korean medicine, arrhythmia subtype classification from the perspective of Korean medicine will be needed for future research.

• 한국자기학회지
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• 제23권3호
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• pp.104-109
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• 2013

소형 영구자석이 부착된 상태에서 요골동맥의 미세한 움직임으로 자기장 변화를 측정하는 홀소자 집게형 맥진기를 개발하였다. 이 맥진기를 통해서 얻은 120명의 임상데이터를 통계적 로지스틱 회귀분석으로 처리하여 허맥과 실맥을 예측하는 알고리즘의 특성을 연구하였다. 요골동맥파의 반사파 시간값과 절흔점 시간값이 허맥과 실맥을 예측할 수 있는 주요인자이였으며, 판별율은 65%이었다. 이로써 한의학적 허맥과 실맥을 예측하고 판별하는 진단지표로 사용할 가능성을 제하였다.