scholarly journals Closed-Loop Identification of Carotid Sinus Baroreflex Transfer Characteristics Using Electrical Stimulation.

2000 ◽  
Vol 50 (3) ◽  
pp. 371-380 ◽  
Author(s):  
Toru Kawada ◽  
Takayuki Sato ◽  
Masashi Inagaki ◽  
Toshiaki Shishido ◽  
Teiji Tatewaki ◽  
...  
1997 ◽  
Vol 273 (2) ◽  
pp. H1024-H1031 ◽  
Author(s):  
T. Kawada ◽  
M. Sugimachi ◽  
T. Sato ◽  
H. Miyano ◽  
T. Shishido ◽  
...  

In the circulatory system, a change in blood pressure operates through the baroreflex to alter sympathetic efferent nerve activity, which in turn affects blood pressure. Existence of this closed feedback loop makes it difficult to identify the baroreflex open-loop transfer characteristics by means of conventional frequency domain approaches. Although several investigators have demonstrated the advantages of the time domain approach using parametric models such as the autoregressive moving average model, specification of the model structure critically affects their results. Thus we investigated the applicability of a nonparametric closed-loop identification technique to the carotid sinus baroreflex system by using an exogenous perturbation according to a binary white-noise sequence. To validate the identification method, we compared the transfer functions estimated by the closed-loop identification with those estimated by open-loop identification. The transfer functions determined by the two identification methods did not differ statistically in their fitted parameters. We conclude that exogenous perturbation to the baroreflex system enables us to estimate the open-loop baroreflex transfer characteristics under closed-loop conditions.


2000 ◽  
Vol 89 (5) ◽  
pp. 1979-1984 ◽  
Author(s):  
Toru Kawada ◽  
Masashi Inagaki ◽  
Hiroshi Takaki ◽  
Takayuki Sato ◽  
Toshiaki Shishido ◽  
...  

Although neck suction has been widely used in the evaluation of carotid sinus baroreflex function in humans, counteraction of the aortic baroreflex tends to complicate any interpretation of observed arterial pressure (AP) response. To determine whether a simple linear model can account for the AP response during neck suction, we developed an animal model of the neck suction procedure in which changes in carotid distension pressure during neck suction were directly imposed on the isolated carotid sinus. In six anesthetized rabbits, a 50-mmHg pressure perturbation on the carotid sinus decreased AP by −27.4 ± 4.8 mmHg when the aortic baroreflex was disabled. Enabling the aortic baroreflex significantly attenuated the AP response (−21.5 ± 3.8 mmHg, P< 0.01). The observed closed-loop gain during simulated neck suction was well predicted by the open-loop gains of the carotid sinus and aortic baroreflexes using the linear model (−0.43 ± 0.13 predicted vs. −0.41 ± 0.10 measured). We conclude that the linear model can be used as the first approximation to interpret AP response during neck suction.


2021 ◽  
Vol 15 ◽  
Author(s):  
Toru Kawada ◽  
Keita Saku ◽  
Tadayoshi Miyamoto

The arterial baroreflex system plays a key role in maintaining the homeostasis of arterial pressure (AP). Changes in AP affect autonomic nervous activities through the baroreflex neural arc, whereas changes in the autonomic nervous activities, in turn, alter AP through the baroreflex peripheral arc. This closed-loop negative feedback operation makes it difficult to identify open-loop dynamic characteristics of the neural and peripheral arcs. Regarding sympathetic AP controls, we examined the applicability of a nonparametric frequency-domain closed-loop identification method to the carotid sinus baroreflex system in anesthetized rabbits. This article compares the results of an open-loop analysis applied to open-loop data, an open-loop analysis erroneously applied to closed-loop data, and a closed-loop analysis applied to closed-loop data. To facilitate the understanding of the analytical method, sample data files and sample analytical codes were provided. In the closed-loop identification, properties of the unknown central noise that modulated the sympathetic nerve activity and the unknown peripheral noise that fluctuated AP affected the accuracy of the estimation results. A priori knowledge about the open-loop dynamic characteristics of the arterial baroreflex system may be used to advance the assessment of baroreflex function under closed-loop conditions in the future.


2020 ◽  
Vol 43 (10) ◽  
pp. 1057-1067 ◽  
Author(s):  
Gean Domingos-Souza ◽  
Fernanda Machado Santos-Almeida ◽  
César Arruda Meschiari ◽  
Nathanne S. Ferreira ◽  
Camila A. Pereira ◽  
...  

1979 ◽  
Vol 12 (8) ◽  
pp. 961-968
Author(s):  
J.A. de la Puente ◽  
P. Albertos

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3653
Author(s):  
Lilia Sidhom ◽  
Ines Chihi ◽  
Ernest Nlandu Kamavuako

This paper proposes an online direct closed-loop identification method based on a new dynamic sliding mode technique for robotic applications. The estimated parameters are obtained by minimizing the prediction error with respect to the vector of unknown parameters. The estimation step requires knowledge of the actual input and output of the system, as well as the successive estimate of the output derivatives. Therefore, a special robust differentiator based on higher-order sliding modes with a dynamic gain is defined. A proof of convergence is given for the robust differentiator. The dynamic parameters are estimated using the recursive least squares algorithm by the solution of a system model that is obtained from sampled positions along the closed-loop trajectory. An experimental validation is given for a 2 Degrees Of Freedom (2-DOF) robot manipulator, where direct and cross-validations are carried out. A comparative analysis is detailed to evaluate the algorithm’s effectiveness and reliability. Its performance is demonstrated by a better-quality torque prediction compared to other differentiators recently proposed in the literature. The experimental results highlight that the differentiator design strongly influences the online parametric identification and, thus, the prediction of system input variables.


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