When measuring the ejection fraction for the evaluation of the ventricular pumping function by means of the thermodilution technique, the slow response a conventional thermistor has caused it to be considered unsuitable, and fast thermistors have been proposed as an alternative. However, in this paper we propose improving the time-domain response of a conventional thermistor using a signal processing technique composed of a series of first-order high-pass filters which is known as the natural observation system. We considered the rise time of the thermistor in response to a step temperature change to effect correction for the measurement of the ejection fraction. The coefficients of the natural observation system were calculated by minimizing the square error between the step-response signal of the thermistor and the band-limited reference signal. In an experiment using a model ventricle, the thermodilution curve obtained from a conventional thermistor was improved using the proposed technique, thus enabling successful measurement of the ejection fraction of the ventricles.

A novel method of multichannel surface EMG processing has been developed to compensate for the distortion in bipolar surface EMG signals due to the movement of innervation zones. The distortion of bipolar surface EMG signals was mathematically described as a filtering function. A compensating technique for such distorted bipolar surface EMG signals was developed for the brachial biceps during dynamic contractions in which the muscle length and tension change. The technique is based on multichannel surface EMG measurement, a method for estimating the movement of an innervation zone, and the inverse filtering technique. As a result, the distorted EMG signals were compensated and transformed into nearly identical waveforms, independent of the movement of the innervation zone.

The pressure waveforms indicated on a catheter manometer system are subject to serious distortion due to the resonance of the catheter itself, or the compliance of a particular transducer. Although several methods have been proposed for improving those characteristics, they ahave never been put into practice. We have focused on the transfer function of the catheter manometer, and made a pilot system, using the natural observation method. This method has been suggested as a means of studying the structure of the instantaneous waveform. In this manner, we were able to increace the bandwidth in the ferquency domain and reduce the ringing in the time domain. Correction was performed automatically, using a step wave. Reproduction of the waveform with a flushing device, was a task of equal simplicity, that allowed us to estimate the system parameters so that the response waveform became step-like. In the experiment, our system provided distortion-free left-ventricular pressure waveform measurements and exact evaluation of the cardiac pumping system. The values obtained came much closer to the original figures arrived at by the catheter-tip manometer system.

In the present paper we shall examine the real-time restoration of biomedical signals under additive noises. Biomedical signals measured by instruments such as catheter manometers, ambulatory electrocardiographs and thermo-dilution sensors are susceptible to distortion and noise. Therefore, such signals must be restored to their original states. In the present study, nonstationary biomedical signals are observed and described using a mathematical model, and several restoration filters that are composed of a series of applications of this model are proposed. These filters restored band-limited approximations of the original signals in real-time. In addition, redundancy is introduced into these restoration filters in order to suppress additive noise. Finally, an optimum filter that accounts for restoration error and additive noise is proposed.

We use the B spline function and apply the Oslo algorithm to minimize the number of control points in electrocardiogram (ECG) waveform compression under the limitation of evaluation indexes. This method is based on dynamic programming matching to transfer the control points of a reference ECG waveform to the succeeding ECG waveforms. This reduces the execution time for beat-to-beat processing. We also reduced the processing time at several compression stages. When the difference percent normalized root mean square difference is around 10, our method gives the highest compression ratio at a sampling frequency of 250 Hz.

In this paper, we present a flexible distributed computing system in which it is very easy to add required computing components at any time. The system is an Internet-based solution, and mainly developed by Java and XML. Moreover, by implementing a new configuration of computing information that is setting up Public Information and Private Information, the system can accommodate various computing requests, and facilitate a flexible design. Additionally, to show the practical merit, as an example of signal processing, we presented how to apply our proposed system to selection of a suitable artificial neural network.

General exercise approaches are not convenient for some people in undertaking appropriate exercise due to the limited variety of present programs at existing exercise machines. Moreover, continuous support by one sports doctor is only available for a limited number of users. In this paper, therefore, we propose an Internet-based technical framework, which is designed on multi-tiered client/server architecture, for integrating and easily upgrading exercise programs. By applying the technical framework, a cycle ergometer health promotion system was developed for providing personally fitted. We also presented some facilities to assist sports doctors in quickly designing and remotely improving individual exercise protocols against cycle ergometer exercise based on a history database. Then we evaluated the Internet-based cycle ergometer system during two months of feasibility experiments for six elderly persons in terms of usability. As a result, the Internet-based cycle ergometer system was effective for continuously supporting the personal fitting procedure.

Adapting the principle of parametron oscillation, a small implantable temperature sensor requiring no internal power supply is described. Since this sensor's oscillation frequency is half that of the excitation frequency, the oscillated signal can be measured from the reception side, free of any signal, interference, simply by positioning the sensor and the excitation antenna so that; 1) they are separated up to 95 cm in the air; 2) a 41 cm gap, the phantom equivalent of the thickness of the human abdomen maintain between them. In the temperature-dependent quartz resonator sensor, oscillation occurs only when frequency and temperature correspond. The excitation power is then adjusted so that the frequency bandwidth narrows. As a result, the margin of error in measuring the temperature is minimized; (0.07).

Myoelectric (ME) signals during dynamic movement suffer from motion arifact noise caused by mechanical friction between electrodes and the skin. It is difficult to reject artifact noises using linear filters, because the frequency components of the artifact noise include those of ME signals. This paper describes a nonlinear method of eliminating artifacts. It consists of an inverse autoregressive (AR) filter, a nonlinear filter, and an AR filter. To deal with ME signals during dynamic movement, we introduce an adaptive procedure and fuzzy rules that improve the performance of the nonlinear filter for local features. The result is the best ever reported elimination performance. This fuzzy rule based adaptive nonlinear artifact elimination filter will be useful in measurement of ME signals during dynamic movement.