The correlation between skin electrical conductance and the score of qi vacuity.
In traditional Chinese medicine, the syndrome of qi vacuity means that the patient's body has a low level of energy to react to stress. Recently, we used a score, the QV score, by scaling the severity of symptoms and signs of qi vacuity in patients with tiredness. The aim of this study was to investigate the relationship between QV score and skin electrical conductance in patients with tiredness. One hundred and forty-three healthy controls and 103 patients with tiredness were involved. Each subject received a weak electrical stimulation with constant voltage (1.75 volt), and conductance was measured between two different limbs. The mean value of skin conductance among four limbs was calculated and expressed by a special unit, namely Chin. The correlation between the skin conductance and QV score was analyzed by a linear regression analysis. The results showed that skin electrical conductance of healthy controls was negatively correlated with age (r-coefficient = -0.51, P = 0.000). The skin conductance of patients with tiredness was significantly lower than that of healthy controls with matching age (P = 0.000 by Student's t-test). Moreover, there was a positive correlation between the decrease of skin conductance and the QV score in patients with tiredness (r-coefficient = +0.68, P = 0.000). These results suggest that a decrease in skin electrical conductance may be closely related to the severity of qi vacuity. The skin conductance test is a simple, reliable, and quantitative method for detection of syndrome of qi vacuity.
Yu
H M
HM
Department of Chinese Medicine, China Medical College Hospital, Taichung, Taiwan.
Chang
H H
HH
Liou
S Y
SY
Li
S F
SF
Hou
M M
MM
Chen
M F
MF
D000328:Adult; D000367:Age Factors; D000368:Aged; D000375:Aging / Q000502:physiology; D005163:Factor Analysis, Statistical; D005221:Fatigue / Q000503:physiopathology; D005260:Female; D005712:Galvanic Skin Response; D006801:Humans; D008297:Male; D008875:Middle Aged; D019413:Qi; D012044:Regression Analysis