Information about the distribution of fluid in tissues is supposed to be quite useful for diagnosing various diseases, for monitoring seriously ill patients, bnd for medical treatment such as hemodialysis (HD), because the distribution of intra- and extra-cellular fluid (ICF & ECF) is affected by circulation, tissue metabolism, electrolytic equilibrium of ICF & ECF and so on.
It is well known that the impedance characteristics of living tissues have three kinds of frequency dispersion, called α, β, γ dispersions, due to different mechanisms of relaxation. Especially, the β dispersion phenomenon known as a structural relaxation can be used for estimating ICF & ECF distribution. The equivalent circuit with multiple time constants is presented as a model of the electrical properties of tissues near β dispersion frequency. It can give the equivalent resistivity RE & RI for ECF & ICF respectively. The frequency characteristics for calculating RE & RI are measured within 5 seconds by a microcomputer.
This paper deals with the frequency characteristics of human legs and arms as measured before and after dialysis and exercise. The body fluid remarkably decreases with dialysis. It has been shown that the ECF volume greatly decreases, but the ICF volume slightly increases by regular dialysis. It is suggested that a part of ECF moves into the cells. With high sodium dialysis, the ECF volume decreases and ICF volume also slightly decreases. These results well agree with the other laboratory data. The impedance before and after exercise has also been measured. The data oftained from ordinary persons are quite different from those of well-trained athletes. It is concluded that this method can be applicable to various clinical purposes.

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We have already developed an eye movement analyzing system using an infrared ray television fundus camera. Though the quality of the eye fundus TV images is not good, the system can measure the eye movement with an accuracy of 0.08 degree. We tried to apply this system to compensating the eye movement in making the retinal sensitivity map. Target mark with variable brightness is presented to various positions of the retina of a subject through a CRT assembled in the infrared ray TV fundus camera. The subject is supposed to respond if he can perceive the target mark. The TV image of the eye fundus with overlayed target mark and response sign is recorded into the U-matic VTR. Then the image of the video tape is analyzed by a computer. We have obtained the retinal sensitivity maps, which show good agreement with the results of Goldmann perimeter.

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The equivalent-dipole method, in which one or more electric dipoles are determined so that they best approximate electrical activities of the heart is one of the representative methods of solving the inverse problem in electrocardiography. Resultant equivalent dipoles are affected by several factors, such as simplification of the human torso, noise in the measured potentials, fluctuations in the reference potential and displacement of the electrode locations.
To investigate the effects of these factors, we performed computer simulations and have come to the following conclusions. (1) Considering the calculation time as well as the precision of the results, the infinite-medium model, in which the body is immersed in a conductor with the same conductivity as that of the inside of the torso, is most suitable. (2) When the potential distributions are measured by 128 electrodes arranged on the chest and the back, dipole estimation error is less than 5mm provided that noise and offset voltage error be 20% of the RMS value of the body surface potential distribution. (3) When the excitation front is located near the body surface, dipole estimation error is comparable to the electrode location error.

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The equivalent cardiac dipole method has been investigated to estimate from a body surface potential distribution the location as well as the vector components of a dipole, which approximate the EMF sources in a heart. However, the single dipole approximation is not always valid, and two or more dipoles should be taken into account for complicated EMF sources.
To look into the accuracy of the estimation of two cardiac dipoles, we performed computer simulation with a three dimensional torso model. Several factors which affect the resultant equivalent dipoles, such as simplification of the human torso, noise in the measured potentials, fluctuations in the reference potential and displacements of the electrode locations, have been considered, and the following conclusions were obtained.
(1) To avoid a long computation time in case of clinical application, the human torso must be simplified to approximate such models as a semi-infinite region bounded by a plane, a sphere, or an infinite conductor in which the body is immersed. Among these, the infinite-medium model is most desirable.
(2) The infinite-medium model usually results in bias error ranging from 1cm to 3cm. However, a pair of dipoles located too close to each other are sometimes estimated at completely different positions.
(3) Except for rare occasions in which the estimated dipoles are far from their original locations, the dipole estimation error due to noise and offset voltage fluctuations is less than 5mm if they are 10% of the RMS of the body surface potential distribution.
(4) A 1cm error in electrode locations results in 2cm error in estimated dipole locations.

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