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Multivariate Autoregressive Model Based Heart Motion Prediction Approach for Beating Heart Surgery

机译:基于多元自回归模型的心脏跳动心脏运动预测方法

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A robotic tool can enable a surgeon to conduct off-pump coronary artery graft bypass surgery on a beating heart. The robotic tool actively alleviates the relative motion between the point of interest (POI) on the heart surface and the surgical tool and allows the surgeon to operate as if the heart were stationary. Since the beating heart's motion is relatively high-band, with nonlinear and nonstationary characteristics, it is difficult to follow. Thus, precise beating heart motion prediction is necessary for the tracking control procedure during the surgery. In the research presented here, we first observe that Electrocardiography (ECG) signal contains the causal phase information on heart motion and non-stationary heart rate dynamic variations. Then, we investigate the relationship between ECG signal and beating heart motion using Granger Causality Analysis, which describes the feasibility of the improved prediction of heart motion. Next, we propose a nonlinear time-varying multivariate vector autoregres...
机译:机器人工具可使外科医生在跳动的心脏上进行非体外循环冠状动脉搭桥手术。机器人工具可主动缓解心脏表面上的兴趣点(POI)与手术工具之间的相对运动,并允许外科医生像心脏静止一样进行操作。由于跳动的心脏的运动是相对较高的频带,具有非线性和非平稳的特征,因此很难遵循。因此,精确的跳动心脏运动预测对于手术期间的跟踪控制程序是必要的。在这里提出的研究中,我们首先观察到心电图(ECG)信号包含有关心动和非平稳心率动态变化的因果相位信息。然后,我们使用格兰杰因果关系分析研究了心电图信号与跳动的心脏运动之间的关系,它描述了改进的心脏运动预测的可行性。接下来,我们提出一种非线性时变多元向量自回归...

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