Localization of Point-of-Interest Positions on Cardiac Surface for Robotic-Assisted Beating Heart Surgery.
Localization of Point-of-Interest Positions on Cardiac Surface for Robotic-Assisted Beating Heart Surgery.
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DOI：
10.1109/embc46164.2021.9630917
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发表时间：
2021-11
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机器人辅助心脏不停跳手术的关键部分之一是精确定位心脏表面的兴趣点(POI)位置，这需要由机器人仪器进行跟踪。这是具有挑战性的，因为从其定位POI位置的传入传感器测量可能是噪声和不完整的。本文提出了两种基于贝叶斯滤波的POI位置在线定位方法。具体地，研究了扩展卡尔曼滤波(EKF)和粒子滤波(PF)定位算法来估计POI位置的状态。作者在过去的工作中演示了由广义自适应预测器生成的对即将到来的心脏运动的估计，该估计也被纳入以生成改进的运动模型。用预先记录的活体心脏运动数据对所提出的方法进行了验证。
One of the critical components of robotic-assisted beating heart surgery is precise localization of a point-of-interest (POI) position on cardiac surface, which needs to be tracked by the robotic instruments. This is challenging as the incoming sensor measurements, from which POI position is localized, might be noisy and incomplete. This paper presents two Bayesian filtering based localization approaches to localize POI position online from sonomicrometer measurements. Specifically, extended Kalman filter (EKF) and particle filter (PF) localization algorithms are explored to estimate the state of POI position. The estimations of upcoming heart motion generated by the generalized adaptive predictor, which is demonstrated in the authors’ past work, are also incorporated to generate an improved motion model. The proposed methods are validated with prerecorded in-vivo heart motion data.