Biomedical subjects

E Furutani

Publications and source records attributed to E Furutani.

3 recordsLinked to original sources

PubMed1999

Clinical application of a blood pressure autoregulation system during hypotensive anesthesia.

A blood pressure autoregulation system based on the state-predictive control method was developed to minimize intraoperative blood loss and hence avoid blood transfusion. In this report, the system is further improved by incorporating fuzzy logic with a fail-safe function and an individual parameter-identifying function. The safety and stability of this system had been confirmed by preclinical experiments with dogs. Thereafter clinical application with 17 patients was conducted to maintain their mean arterial pressure at around 60 mmHg during major surgery. The use of this system resulted in decreased blood loss and more speedy and accurate surgery due to a clearer surgical field. Unwanted effects of hypotension were not observed clinically or in laboratory tests. This system is therefore safe, stable, and effective in reducing the blood loss during major surgery that otherwise might cause substantial blood loss.

Anesthesia↗

PubMed1995

Blood pressure control during surgical operations.

In order to reduce intraoperative blood loss and spare blood transfusion, we developed a blood pressure control system using a state-predictive controller. Using adult mongrel dogs, the mean arterial pressure (MAP) was recorded from a femoral artery while trimethaphan camsilate was infused at constant rates. A pure delay plus a first-order delay model was then derived from the dose-response curves and the values of plant parameters (gain, time-constant, dead-time, and so on) were estimated based on the experimental data. For this model, a state-predictive servo system was designed to cope with the pure delay existing in the model, and simulated. In order to evaluate the accuracy and reliability of this system, we experimented on dogs. With a reference MAP set at 60 mmHg, the MAP reached the reference level in 5.8 to 26.5 min. The duration of error from the reference MAP (+/- 10%) was 2.3 +/- 3.9 min/h (n = 7). These results indicated the safety and stability of our system.

Animals↗

PubMedDate not supplied

Novel control system for blood glucose using a model predictive method.

We developed a novel blood glucose control system, using a model predictive method, to achieve optimal control of the blood glucose level in severely diabetic or pancreatectomized patients. This system is designed to predict glucose level changes in advance, considering delayed response time and the administered doses of insulin. This method is also designed to calculate the most appropriate insulin infusion rate by considering differences in individual response to insulin. In this study, we compared our system with a conventional proportional and differential controller (PD controller) to determine whether the new system could regulate the glucose level efficiently in pancreatectomized dogs. The model predictive control method resulted in a significant reduction of mean insulin infusion rate compared with the conventional PD controller (0.71 mU/kg per min vs. 1.81 mU/kg per min, p = 0.0005), when the glucose level in both methods reached the planned target level (100 mg/dl). The new system also tended to have a reduced mean glucose infusion rate for compensating for overshooting of the glucose level compared with the PD controller (0.7 mg/kg per min vs. 1.1 mg/kg per min, p = 0.16). These results indicate that the new system should be a useful tool for regulating the glucose level in severely diabetic patients.

Animals↗