Laboratoire des Sciences de l'Image, de l'Informatique et de la Télédétection (LSIIT), University of Strasbourg, Strasbourg, France.
IEEE Trans Biomed Eng. 2009 Nov;56(11):2551-63. doi: 10.1109/TBME.2009.2026054. Epub 2009 Jun 26.
Off-pump totally endoscopic coronary artery bypass grafting is a milestone for cardiac surgery, and still a technical challenge. Indeed, the fast and complex cardiac motion makes this operating method technically demanding. Therefore, several robotic systems have been designed to assist the surgeons by compensating for the cardiac motion and providing a virtually motionless operating area. In the proposed systems, the servoing schemes often take advantage of a prediction algorithm that supplies the controller with some future heart motion. This prediction enlarges the control-loop bandwidth, thus allowing a better motion compensation. Obviously, improving the prediction accuracy will lead to better motion-compensation results. Thus, a current challenge in computer-assisted cardiac surgery research is the design of efficient heart-motion-prediction algorithms. In this paper, a detailed survey of the main existing prediction approaches is given and a classification is provided. Then, a novel prediction technique based on amplitude modulation is proposed, and compared with other techniques using in vivo collected datasets. A final discussion summarizes the main features of all the proposed approaches.
不停跳全内窥镜冠状动脉旁路移植术是心脏外科的一个里程碑,仍然是一项技术挑战。事实上,快速而复杂的心脏运动使得这种手术方法具有很高的技术要求。因此,已经设计了几种机器人系统来通过补偿心脏运动并提供几乎无运动的操作区域来帮助外科医生。在所提出的系统中,伺服系统通常利用预测算法为控制器提供一些未来的心脏运动。该预测扩大了控制回路带宽,从而实现更好的运动补偿。显然,提高预测精度将导致更好的运动补偿结果。因此,计算机辅助心脏手术研究中的一个当前挑战是设计有效的心脏运动预测算法。本文详细调查了主要的现有预测方法,并进行了分类。然后,提出了一种基于调幅的新型预测技术,并使用体内采集的数据集与其他技术进行了比较。最后的讨论总结了所有提出方法的主要特点。