• The Journal of the Society of Korean Medicine Diagnostics
• /
• v.10 no.1
• /
• pp.109-140
• /
• 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
• /
• v.8 no.1
• /
• pp.63-72
• /
• 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
• /
• v.23 no.1
• /
• pp.15-36
• /
• 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
• /
• v.1 no.2
• /
• pp.134-138
• /
• 2006

Depression is the most common and widespread mood disorder. About 20% of the population might suffer a major, incapacitating episode of depression during their lifetime. This disorder can be classified into two types: major depressive disorders and bipolar disorder. Since pharmaceutical treatments are different according to types of depression disorders, correct and fast classification is quite critical for depression patients. Yet, classical statistical method, such as minnesota multiphasic personality inventory (MMPI), have some difficulties in applying to depression patients, because the patients suffer from concentration. We used electroencephalogram (EEG) analysis method fer classification of depression. We extracted nonlinearity of information flows between channels and estimated approximate entropy (ApEn) for the EEG at each channel. Using these attributes, we applied two types of data mining classification methods: decision tree and possibilistic support vector machines (PSVM). We found that decision tree showed 85.19% accuracy and PSVM exhibited 77.78% accuracy for classification of depression, 30 patients with major depressive disorder and 24 patients having bipolar disorder.