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Non-invasive estimation and control of inlet pressure in an implantable rotary blood pump for heart failure patients

机译:心力衰竭患者植入式旋转血泵的无创估计和入口压力控制

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We propose a dynamical model for mean inlet pressure estimation in an implantable rotary blood pump during the diastolic period. Non-invasive measurements of pump impeller rotational speed (ω), motor power (P), and pulse width modulation signal acquired from the pump controller were used as inputs to the model. The model was validated over a wide range of speed ramp studies, including (i) healthy (C1), variations in (ii) heart contractility (C2); (iii) afterload (C2, C3, C4), and (iv) preload (C5, C6, C7). Linear regression analysis between estimated and extracted mean inlet pressure obtained from in vivo animal data (greyhound dogs, N = 3) resulted in a highly significant correlation coefficients (R~2 = 0.957, 0.961, 0.958, 0.963, 0.940, 0.946, and 0.959) and mean absolute errors of (e = 1.604, 2.688, 3.667, 3.990, 2.791, 3.215, and 3.225 mmHg) during C1, C2, C3, C4, C5, C6, and C7, respectively. The proposed model was also used to design a controller to regulate mean diastolic pump inlet pressure using non-invasively measured ω and P. In the presence of model uncertainty, the controller was able to track and settle to the desired input within a finite number of sampling periods and minimal error (0.92 mmHg). The model developed herein will play a crucial role in developing a robust control system of the pump that detects and thus avoids undesired pumping states by regulating the inlet pressure within a predefined physiologically realistic limit.
机译:我们提出了一个动态模型,用于估计舒张期植入式旋转血泵中的平均入口压力。从泵控制器获取的泵叶轮转速(ω),电机功率(P)和脉宽调制信号的非侵入式测量值用作模型的输入。该模型已在广泛的速度斜坡研究中得到验证,包括(i)健康(C1),(ii)心脏收缩力(C2)的变化; (iii)后加载(C2,C3,C4),以及(iv)预加载(C5,C6,C7)。从体内动物数据(灵狗,N = 3)获得的估计和提取的平均入口压力之间的线性回归分析得出了非常显着的相关系数(R〜2 = 0.957、0.961、0.958、0.963、0.940、0.946和0.959) )和平均绝对误差(e = 1.604、2.688、3.667、3.990、2.791、3.215和3.225 mmHg)在C1,C2,C3,C4,C5,C6和C7期间分别出现。所提出的模型还用于设计控制器,该控制器使用非侵入式测量的ω和P来调节平均舒张压泵入口压力。在存在模型不确定性的情况下,控制器能够在有限的范围内跟踪并稳定至所需输入。采样周期和最小误差(0.92 mmHg)。本文开发的模型将在开发泵的鲁棒控制系统中发挥至关重要的作用,该系统通过将入口压力调节在预定的生理现实极限内来检测并避免不希望的泵送状态。

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