Heart Motion Prediction Based on Adaptive Estimation Algorithms for Robotic-Assisted Beating Heart Surgery

Tuna, E. Erdem; Franke, Timothy J.; Bebek, Özkan; Shiose, A.; Fukamachi, Kiyotaka; Çavuşoğlu, M. Cenk

doi:10.1109/tro.2012.2217676

Cited by 52 publications

(74 citation statements)

References 23 publications

(58 reference statements)

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“…Active deformable objects, in which the objects have active internal forces are outside the scope of the present study. Manipulation of active deformable objects, such as manipulation of a beating heart in robotic cardiac surgery (Nakamura et al, 2001; Bebek and Çavuşoğlu, 2007; Yuen et al, 2009; Richa and Poignet, 2009; Tuna et al, 2013), brings interesting challenges. As the active internal forces result in non-random perturbations, they would need to be explicitly modeled to avoid systematic errors in the probabilistic algorithm.…”

Section: Discussionmentioning

confidence: 99%

Identification and active exploration of deformable object boundary constraints through robotic manipulation

Boonvisut

Çavuşoğlu

2014

The International Journal of Robotics Research

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Robotic motion planning algorithms for manipulation of deformable objects, such as in medical robotics applications, rely on accurate estimations of object deformations that occur during manipulation. An estimation of the tissue response (for off-line planning or real-time on-line re-planning), in turn, requires knowledge of both object constitutive parameters and boundary constraints. In this paper, a novel algorithm for estimating boundary constraints of deformable objects from robotic manipulation data is presented. The proposed algorithm uses tissue deformation data collected with a vision system, and employs a multi-stage hill climbing procedure to estimate the boundary constraints of the object. An active exploration technique, which uses an information maximization approach, is also proposed to extend the identification algorithm. The effects of uncertainties on the proposed methods are analyzed in simulation. The results of experimental evaluation of the methods are also presented.

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Section: Discussionmentioning

confidence: 99%

Identification and active exploration of deformable object boundary constraints through robotic manipulation

Boonvisut

Çavuşoğlu

2014

The International Journal of Robotics Research

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“…For instance, the use of sonomicrometry crystals, small crystals that are sutured to the heart, is well suited to evaluating the surgical system [10], [11], [12], but is not practical in the operating room. In addition, significant computation is required to analyze the raw sensor data, making this method not suitable for real-time applications.…”

Section: ) Non-image-based Methodsmentioning

confidence: 99%

GPC-based teleoperation for delay compensation and disturbance rejection in image-guided beating-heart surgery

Bowthorpe

Garcia

Tavakoli

2014

2014 IEEE International Conference on Robotics and Automation (ICRA)

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Abstract-Beating-heart surgery is not currently possible for most surgical procedures as it requires superhuman skill to manually track the heart's motion while performing a surgical task. However, if a surgical tool could track the motion of the point of interest (POI) on the heart, then, with respect to the surgical tool tip the POI would appear stationary. Such a system can be created with a teleoperated surgical robot that is controlled to track the combination of the heart's and the surgeon's motion, as input through a separate user console. To develop such a system, the motion of the heart is found in ultrasound images where the image acquisition introduces delays of approximately 40 ms and image processing further increases this delay. Directly using this delayed position measurement in the feedback control loop can lead to instability and poor tracking. The generalized predictive controller used in this work compensates for this time delay despite large disturbances with velocities up to 210 mm/s and accelerations up to 3800 mm/s 2 caused by the moving heart.

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“…In this study, two distinct types of experimentally collected heart data [23] are used. The first type includes constant heart rate data, whereas the second type includes varying heart rate data.…”

Section: Heart Motion Nonlinear Predictionmentioning

confidence: 99%

A Quadratic Nonlinear Prediction-Based Heart Motion Model following Control Algorithm in Robotic-Assisted Beating Heart Surgery

Meng

2013

International Journal of Advanced Robotic Systems

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Off-pump coronary artery bypass graft surgery outperforms the traditional on-pump surgery because the assisted robotic tools can cancel the relative motion between the beating heart and the robotic tools, which reduces post-surgery complications for patients. The challenge for the robot assisted tool when tracking the beating heart is the abrupt change caused by the nonlinear nature of heart motion and high precision surgery requirements. A characteristic analysis of 3D heart motion data through bi-spectral analysis demonstrates the quadratic nonlinearity in heart motion. Therefore, it is necessary to introduce nonlinear heart motion prediction into the motion tracking control procedures. In this paper, the heart motion tracking problem is transformed into a heart motion model following problem by including the adaptive heart motion model into the controller. Moreover, the model following algorithm with the nonlinear heart motion model embedded inside provides more accurate future reference by the quadratic term of sinusoid series, which could enhance the tracking accuracy of sharp change point and approximate the motion with sufficient detail. The experiment results indicate that the proposed algorithm outperforms the linear prediction-based model following controller in terms of tracking accuracy (root mean square).

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Heart Motion Prediction Based on Adaptive Estimation Algorithms for Robotic-Assisted Beating Heart Surgery

Cited by 52 publications

References 23 publications

Identification and active exploration of deformable object boundary constraints through robotic manipulation

Identification and active exploration of deformable object boundary constraints through robotic manipulation

GPC-based teleoperation for delay compensation and disturbance rejection in image-guided beating-heart surgery

A Quadratic Nonlinear Prediction-Based Heart Motion Model following Control Algorithm in Robotic-Assisted Beating Heart Surgery

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