• 대한한의진단학회지
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• 제10권1호
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• pp.109-140
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• 2006

Background: In practicing qigong, People must achieve three Points : adjust their Posture, control their breathing and have a peace of mind. That is, Cho-Sin [調身] , Cho-Sik [調息] , Cho-Sim [調心] . Slow respiration is the important pattern of respiration to improve the human health. However, unsuitable breathing training have been occurred to mental disorder such as insomnia, anorexia etc. So, we think that the breathing training to consider the individual variations are desired. Objectives: We performed this study to examine the physiological effects of controlled respiration on the normal range of frequency domain electroencephalogram(EEC) in healthy subjects Also, to study examine individual variations according to the physiological effects between controlled respiration and Han-Yeol [寒熱] , respiration period, gender and age-related groups on the EEC in healthy subjects. Methods: When the subjects controlled the time of breathing (inspiration and expiration time) consciously, compared with natural respiration, and that their physiological phenomena are measured by EEC. In this research we used breathing time as in a qigong training (The Six-Word Excise) and observed physiological phenomena of the controlled natural respiration period with the ratio of seven to three(longer inspiration) and three to seven(longer expiration) . We determined, heat-cold score by Han-Yeol [寒熱] questionnaire, average of natural respiration period, according to decade, EEC of 140 healthy subjects (14 to 68 years old; 38 males, 102 females) by means of alpha, beta spectral relative power. Results: 1) In Controlled respiration compared with the natural respiration, ${\alpha}\;I\;(Fp2)\;and\;{\beta}$ I (Fpl, Fp2, F3, F4) decreased on the EEC. 2) In controlled respiration compared with the natural respiration, ${\beta}$ I (Fpl, Fp2, F3, F4) increased with cold group, ${\alpha}/{\beta}$(F3) decreased with heat group, ${\alpha}$ I (Fp2)increased with cold group in longer inspiration. But by means of compound effects, ${\alpha}$ II(F3) increased with cold group in longer inspiration, the other side ${\alpha}$ I (F3) decreased with heat group in controlled respiration on the EEC. 3) In controlled respiration compared with the natural respiration, ${\alpha}$ I (Fp2) decreased with decreased-respiratory-rate(D.R.R.) group, ${\beta}$ I (Fpl, Fp2, F3, F4) increased with D.R.R. and D.R.R. groups, ${\alpha}/{\beta}$(F3) decreased with D.R.R. group. But by means of compound effects, in controlled respiration compared with the natural respiration, ${\alpha}/{\beta}$(F3) decreased with D.R.R. group on the EEG. 4) In controlled respiration compared with the natural respiration, ${\beta}$ I (Fpl, F3, F4) increased with female cup, ${\beta}$ I (Fp2) increased with male and female groups, ${\alpha}/{\beta}$(F3) decreased with male group. But by means of compound effects, in controlled respiration compared with the natural respiration, ${\alpha}$ I (Fp2) increased with female group on the EEC. 5) Compared with the natural respiration, in longer expiration ${\alpha}$ I (Fp2) increased in their forties group, in longer inspiration ${\alpha}$ I (Fp2) increased in their fifties group. But by means of compound effects, in controlled respiration compared with the natural respiration, ${\beta}$ I (Fpl) decreased in teens group on the EEG.

• Biomolecules & Therapeutics
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• 제8권1호
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• pp.63-72
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• 2000

We intended to show some basic requirements for spectrum analysis of electroencephalogram (EEG) by visualizing the differences of the results according to different values of some parameters for analysis. Spectrum analysis is the most popular technique applied for the quantitative analysis of the electroen- cephalographic signals. Each step from signal acquisition through spectrum analysis to presentation of parameters was examined with providing some different values of parameters. The steps are:(1) signal acquisition; (2) spectrum analysis; (3) parameter extractions; and (4) presentation of results. In the step of signal acquisition, filtering and amplification of signal should be considered and sampling rate for analog-to-digital conversion is two-time faster than highest frequency component of signal. For the spectrum analysis, the length of signal or epoch size transformed to a function on frequency domain by courier transform is important. Win dowing method applied for the pre-processing before the analysis should be considered for reducing leakage problem. In the step of parameter extraction, data reduction has to be considered so that statistical comparison can be used in appropriate number of parameters. Generally, the log of power of all bands is derived from the spectrum. For good visualization and quantitative evaluation of time course of the parameters are presented in chronospectrogram.

• Korean Journal of Acupuncture
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• 제23권1호
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• pp.15-36
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• 2006

Objectives . The aim of this study was to examine the effect of electroacupuncture(EA) at the ST36 on normal humans by using power spectral analysis. Methods : EEG(Electroencephalogram) power spectral exhibits site-specific and state-related differences in specific frequency bands. In this study, power spectrum was used as a measure of complexity. 32 channel EEG study was carried out in 12 subjects (10 males; age=26.7 years old, 2females; age=28 years old). Results ; In ${\alpha}$ (alpha) band, the power values at Fp2, F7, F3, Fz, FTC1, FTC2, T3, C3, Cz, C4, TT1, TCP1, CP1, CP2,T5, P3, Pz, P4, Po1, Po2, O1, Oz,O2 channels(p<0.05) during the ST36-acupoint treatment were significantly increased. In ${\beta}$ (beta) band, the power values at Fp2, F7, F3, Fz, F4, F8, FTC1, FTC2, T3, C3, Cz, C4, TT1, TCP1, CP1, CP2, T5, P3, Pz, P4, Po1, Po2, O1, Oz, O2 channels(p<0.05) during the ST36-acupoint treatment were significantly decreased. In ${\delta}$ (delta) band, the power values at F7, Fz, T3, C3, TT1, TCP1, CP1, CP2, T5, P3, Pz,T6, Po1, PO2,O1, Oz, O2 channels(p<0.05) during the ST36-acupoint treatment were significantly decreased. In ${\theta}$(theta) band, the power values at F7, Fz, FTC1, T3, TCP1, CP2, TCP2, Po1, Po2 channels(p<0.05) during the ST36-acupoint treatment were significantly decreased. ${\alpha}$/${\beta}$ values at Cz, T5, O1, Oz, O2 channels during the ST36-acupoint treatment were increased. ${\beta}$/${\theta}$ values at Fpl, F7, F3, Fz, F4, F8, FTC1, FTC2, T3, C3, C4, T4, TT1, TCP1, TCP2, TT2, P3, P4, T6, Pol channels during the ST36-acupoint treatment were increased. Conclusions : This results suggest that Electroacupuncture at the ST36 mostly affects the charge on alpha(23 channels), beta(25 channels) bands.

• Bioinformatics and Biosystems
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• 제1권2호
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• pp.134-138
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• 2006

우울증은 가장 유병율이 높은 '기분 장애'(mood disorder)의 일종으로, 약 20%의 인구가 일생동안 우울증 증상을 한번쯤 경험한다. 이러한 우울증은 크게 '우울 장애'(major depressive disorder)와 '양극성 장애'(bipolar disorder)로 구분된다. 환자의 질병 분류에 따라 사용되는 약과 의학적 처방이 다르기 때문에, 우울증 환자의 빠르고 정확한 진단 및 분류는 매우 중요하다. 기존의 다면성 인성검사(MMPI)와 같은 통계적인 방법이 우울증 환자의 진단을 위해 사용돼 왔으나, 장시간의 집중력을 요구하기 때문에 집중력 저하의 특징을 보이는 우울증 환자들에게 적용하는데 어려움이 있다. 이 논문에서는 이러한 문제를 해결하고자, 빠른 측정이 가능하고 측정동안 집중력을 요하지 않는 EEC 데이터의 분석을 통해 우울증 환자의 분류를 시도하였다. EEG 채널 간 정보 흐름에서의 비선형성과 근사 엔트로피(approximate entropy)의 크기를 속성(attribute)으로 사용하여 데이터 마이닝 기법 중 의사 결정 트리(decision tree)와 가능성 기반 서포트 벡터머신(possibilistic support vector machines) 통해 분석을 수행하였다. 30명의 주요 우울장애환자와 24명의 양극성 장애 환자를 통해 위의 분석을 수행한 결과 의사 결정 트리의 경우 85.19% 의 정확도를 가지며 분류해냈고, 가능성 기반 서포트 벡터머신의 경우 77.78%의 정확도를 보여줬다. 본 연구는 가능성 기반 서포트 벡터 머신 분석이 우울증 환자는 진단하고 분류하는데 유용하게 적용될 수 있는 가능성을 제시하고 있다.