Medical advances include research discoveries and engineering innovations from the space medical program applied to major medical problems. Space miniaturization techniques have been applied to transmitters for various sensors of physiological instruments.
These ingenious techniques remove and enhance medical researches, an organization similarly devoted to applying the fruits of high-technology aerospace industry to the solving of medical problems.
By definition, telemetry is measurement at a distance. It is part of much larger medical communications, which cover the transfer of any information between any two points. The present and the future potential for telemetry and it may be helpful to take a look at representative requirements and typical installations in hospitals; at regional medical programmes; environmental biology; ambulance services; medical information systems and so on.
Small sensors, and tiny transducers are available for patient monitoring systems and are being tested by physicians to advance knowledge of cardiac functions.
All the above-mentioned requirements will not be met from one day to another, but the effort can help to save lives. The methods exist; we have to learn to use them.

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This paper examines, in a digital computer simulated nerve cell, the property of information processing established at synaptic level. To clarify this property, the information theory is applied under the consideration that information is carried not simply by the mean frequency or rate but by the detailed sequence of spikes themselves. The information H (Y) for the response distribution is a measure for the description of the input-output frequency transfer characteristic and the average mutual information I (X₁, ₂ : Y) is that of the pattern sensitive characteristic of successive impulses intervals. With the use of these measures, following results were obtained :
a) When the pre-synaptic form varies from exponential to gamma of order 10, H (Y) becomes larger in the order of gamma of order 10, gamma of order 5, gamma of order 3, gamma of order 2 and exponential. b) The average mutual information I (X₁, ₂ : Y) is closely related to the EPSP size, the pre-synaptic mean frequency and form.
In the relation between EPSP size and pre-synaptic mean frequency at which I (X₁, ₂ : Y) is maximum, the value of the EPSP size decreases as that of the pre-synaptic mean frequency increases. This tendency is common to all pre-synaptic forms.
At all EPSP sizes A₀=0-1.0, each input mean frequency at which I (X₁, ₂ : Y) is maximum becomes higher in the order of exponential, gamma of order 2, gamma of order 3, gamma of order 5 and gamma of order 10.

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Quantitative data in relation to diagnostic information were obtained from scintiscan matrices by digital computer. The data, from scintillation scanner through punched tape were smoothed by the moving average method, and the perimeter of thyroid was decided from histogram of smoothed data, and then counts were normalized from 0 to 10. Thyroid was divided into right and left lobes from maximum and minimum points of curvature of the perimeter.
About each lobe individually, features such as uptake of radioactive iodine, quantification of 131I distribution, difference of 1311 distribution between right and left lobes, area of thyroid, ratio of the longest and the shortest diameters, and perimeter irregularity quantitated by circle fitting to the perimeter were extracted and by using decision tree combined with linear discriminant function, thyroid scintigrams were classified into eight categories. These categories are normal, hyperthyroidism, hot nodule, small defect in lobe, large defect of unilateral lobe, large defect of both lobes, complete defect of unilateral lobe and low uptake.
By this method, about 85% of pathological information on thyroid was correctly abstracted.

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Questionnaires used generally at present are so numerous that they are troublesome both for patients and physicians. To solve this problem, the following method is introduced.
The feature evaluation function is determined on the basis of the idea of minimizing the upper bound of mean error probability in Neyman-Pearson Decision Rule. According to this determined evaluation function, each inquiry is evaluated and ranked in its degree of contribution to discriminating diseases. That is to say, m-number of inquiries are to be selected from among n-number of inquiries, thus reducing them from n to m.
The problem is how to deal with false positive and false negative in case of discriminating diseases. A decision rule capable of controlling the ratio between the two was proposed.
In order to evaluate above-mentioned two theories, the rule was applied to discriminating healthy persons from patients with heart-diseases. The result was, as far as these theories were concerned, satisfactory.

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Design consideration and performed results are described on the measurement circuit with operational amplifier for glass microelectrode bridge, which is frequently used in physiological research. In this system the signal source resistances of the differential amplifier are extremely unbalanced. The frequency band of the discrimination factor is widened by the following scheme in over-all system containing bridge circuit and differential amplifier.
1) Voltage follower type amplifier serves as an impedance transformer from high-impedance unbalance to low-impedance balance.
2) Negative capacitance technique is used for the purpose of extending the frequency band in the high resistance channel.
3) The second order compensation circuit is inserted in the low resistance channel to balance the signals of the two channels.
4) A shield pipe for high resistance (1 000 MΩ) is designed to guarantee pure resistance characteristic for wide frequency range and to avoid capacitance coupling with other circuitry.
Some experimental results are also shown on the artificially cultivated spinal ganglion cell as an example of the application of this equipment.

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This paper presents a theoretical model of sequential diagnosis system by using reduction theory and evaluates the model by applying it to practical problems.
In diagnosis the physician's action is divided into three different processes. They are; 1) to calculate probabilities of a certain disease from information the patient gives about his condition; 2) to name the disease referring to the probabilities; and 3) if it can not be named, to make another approach. Therefore, when we systemize diagnosis, above-mentioned three processes should be taken into consideration and the system should be sequential In this paper, in order to simulate diagnosis system, we select three cases (normal, hypertension, myocardial infarction) and model most basic sequential diagnosis system using TSS-small-computer. We refer to Bayes' Theorem to calculate probabilities of a disease. Criterion for decision-making is set at certain probability. When one of the three cases exceeds this criterion, it is decided as normal (or H or MI). Test selection function selects certain inquiries which are in some order based on the reduction theory developed by Ichino and Kabsawa. The result : with the criterion set at 0.98 and with average 7 inquiries and average 6-minute-diagnosis, the disease decision was successful in 90% of cases. To model the diagnosis system for more than 3 cases is, therefore, desirable and it is expected to have great possibilities.

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