Brain hypothermia requires controlling its temperature within an appropriate range, considering the change of body temperature in a long period. Various mathematical models have been used for the study of control and cooling capability of brain temperature in hypothermia. In the previous models, a hemisphere in a lumped parameter of a uniform temperature has been assumed as a simplified brain without considering the temperature distribution. In the present study, however, a new model is proposed to visualize the temperature distribution in the brain. The model has an approximate shape of each organ in a head based on MRI data, and may well reflect the properties such as heat transfer coefficients, metabolic heat production and heat capacity of human organs. The model has a pseudo-blood-flow model in which any temperature can be set as initial value at the starting place of blood flow. Some simulations using this model are performed with its controlled temperature by the introduction of Ringer's solution into any of the four arteries to the brain. The results of simulation suggests that the various cooling effects are made clear in every region of brain, and that the temperature distribution can be known for the application of controlling brain temperature in a concerning part.

The mathematical simulations are provided for the development of devices and/or methods for medical brain hypothermal treatment. The mathematical model reflecting thermal property of human head was presented as a group of particles consisting of small nodes. By using our mathematical model of head, a new appropriate brain cooling pattern is proposed for the temperature control in selective brain hypothermia, when its temperature rises owing to the increasing productive and accumulating heat by brain injuries. The clinical effectiveness of the new cooling pattern with less consumption of energy is given for the control of brain temperature by using our model of particles of nodes.

In order to understand mechanisms of oculomotor control systems, an oculomotor model based on eye's anatomical structure and physiological mechanism is developed. In this model, various types of eye movements are considered, and two learning systems, one based on adaptive characteristics of #occulus and the other on vestibular nuclei's are developed. The role of neural paths from ocular muscle stretch receptors into #occulus, which were thought to not contribute in eye movement, is discussed in detail from the viewpoint of system control engineering. The experimental results through simulation show good control performance of the proposed model.

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Automatic control systems of brain temperature for water surface-cooling were first-ever applied to the brain hypothermic treatment of patients. A patient in ICU was regarded as a unity controlled system with an input (temperature of water into blanket) and an output (tympanic membrane temperature). The proposed algorithm of optimal-adaptive and fuzzy control laws inclusive of our developed cooling and warming machine were well confirmed during the hypothermic course to keep brain temperature of patients within its allowable range. It was well controlled without much influence due to room temperature, metabolic and circulatory change caused by various medical treatments including the effect of nonlinear and timevarying characteristics of individual patients. The clinical control of brain temperature was almost continuously performed in around 10 days, under the brain temperature between 35 • C and 37 • C scheduled by physicians according to the state of patients. Their state had been monitored during the therapeutic course of pharmacological treatment with almost everyday examinations by CT imaging, referring various vital signs inclusive of the temperature of urinary bladder with continuous measurement of intracranial pressure by a catheter placement in cerebral sinus. The patients had good recovery to their rehabilitation after mild hypothermia by the proposed automatic control systems.