Browsing by Author "Çavuşoğlu, M. C."

Now showing 1 - 5 of 5

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Calibration of 2D ultrasound in 3D space for robotic biopsies
(IEEE, 2015) Ahmad, A.; Çavuşoğlu, M. C.; Bebek, Özkan; Mechanical Engineering; BEBEK, Özkan
Freehand Ultrasound technique is widely used in intraoperative biopsy procedures for detecting the volumes of interest. Freehand ultrasound probe is faster and flexible with 6 degrees of freedom. Thats why the imaging system must be calibrated in 3D space before integrating it with Robotics Biopsy System. In this paper we present a 3D space calibration method using a multipoint cross-wire phantom. The Ultrasound probe is attached to a robotic manipulator arm which moves it over the phantom in precise steps of distances and angles. The position and orientation of the probe is tracked by an optical tracking system. Optical markers are placed on the probe, phantom tank and the validation needle. The optical tracking system returns the position and orientation of the reference frames attached to these optical markers. The location of threads with reference to the frame of Ultrasound probe is found using this information. These values and the values returned by a mathematical model of the calibration box are used to construct the calibration matrix. The whole system is automated so it can process high number of frames which makes it rapid and more accurate. This process is used to calibrate the space for an automated needle insertion biopsy robot. The accuracy of the system was checked by a validation needle in 3D space. RMS error of the experiment groups on average was 1.67mm.
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Design of a parallel robot for needle-based interventions on small animals
(IEEE, 2013-02) Bebek, Özkan; Hwang, M. J.; Çavuşoğlu, M. C.; Mechanical Engineering; BEBEK, Özkan
In this paper, a novel 5-degrees-of-freedom robot for performing needle-based interventions on small animal subjects is presented. The robot can realize dexterous alignment of the needle using two parallel mechanisms, and has a syringe mechanism to insert needles to subjects. Operations on small animals require high accuracy positioning during needle insertion. The kinematic calibration procedure of the robot using an optical tracker as an external sensor is presented to enhance accuracy of the system. After the kinematic calibration, the positioning accuracy of the needle tip is measured as 0.4 mm RMS. The robot design is light weight, and has a motion bandwidth of 4 Hz. The robot can track reference trajectories with a closed-loop controller.
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Heart motion prediction based on adaptive estimation algorithms for robotic assisted beating heart surgery
(IEEE, 2013) Tuna, E. E.; Franke, T. J.; Bebek, Özkan; Shiose, A.; Fukamachi, K.; Çavuşoğlu, M. C.; Mechanical Engineering; BEBEK, Özkan
Robotic-assisted beating heart surgery aims to allow surgeons to operate on a beating heart without stabilizers as if the heart is stationary. The robot actively cancels heart motion by closely following a point of interest (POI) on the heart surface - a process called active relative motion canceling. Due to the high bandwidth of the POI motion, it is necessary to supply the controller with an estimate of the immediate future of the POI motion over a prediction horizon in order to achieve sufficient tracking accuracy. In this paper, two least-squares-based prediction algorithms, using an adaptive filter to generate future position estimates, are implemented and studied. The first method assumes a linear system relation between the consecutive samples in the prediction horizon. On the contrary, the second method performs this parametrization independently for each point over the whole the horizon. The effects of predictor parameters and variations in heart rate on tracking performance are studied with constant and varying heart rate data. The predictors are evaluated using a three-degree-of-freedom (DOF) test bed and prerecorded in vivo motion data. Then, the one-step prediction and tracking performances of the presented approaches are compared with an extended Kalman filter predictor. Finally, the essential features of the proposed prediction algorithms are summarized.
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A personal navigation system using mems-based high-density ground reaction sensor array and inertial measurement unit
(IEEE, 2015) Guo, Q.; Bebek, Özkan; Çavuşoğlu, M. C.; Mastrangelo, C. H.; Young, D. J.; Mechanical Engineering; BEBEK, Özkan
This paper describes a prototype personal navigation system developed for position tracking under GPS denied environments by employing a commercial inertial measurement unit (IMU) and a MEMS-based ground reaction sensor array (GRSA). The GRSA is used to provide zero-velocity updating for the IMU. A Kalman filter further estimates the IMU output bias during the zero-velocity period, which is then removed from the IMU's subsequent output signals to improve the navigation accuracy. Seven 10-minute square-loop walking tests were performed to achieve an in-plane navigation accuracy ranging from 0.4 meter to 3.4 meter with a vertical position accuracy of approximately 1 meter. A further improved performance over an extended navigation time is expected through enhancing the GRSA sensitivity.
Open Access
Towards active tracking of beating heart motion in the presence of arrhythmia for robotic assisted beating heart surgery
(Plos, 2014-07-21) Tuna, E. E.; Karimov, J. H.; Liu, T.; Bebek, Özkan; Fukamachi, K.; Çavuşoğlu, M. C.; Mechanical Engineering; BEBEK, Özkan
In robotic assisted beating heart surgery, the control architecture for heart motion tracking has stringent requirements in terms of bandwidth of the motion that needs to be tracked. In order to achieve sufficient tracking accuracy, feed-forward control algorithms, which rely on estimations of upcoming heart motion, have been proposed in the literature. However, performance of these feed-forward motion control algorithms under heart rhythm variations is an important concern. In their past work, the authors have demonstrated the effectiveness of a receding horizon model predictive control-based algorithm, which used generalized adaptive predictors, under constant and slowly varying heart rate conditions. This paper extends these studies to the case when the heart motion statistics change abruptly and significantly, such as during arrhythmias. A feasibility study is carried out to assess the motion tracking capabilities of the adaptive algorithms in the occurrence of arrhythmia during beating heart surgery. Specifically, the tracking performance of the algorithms is evaluated on prerecorded motion data, which is collected in vivo and includes heart rhythm irregularities. The algorithms are tested using both simulations and bench experiments on a three degree-of-freedom robotic test bed. They are also compared with a position-plus-derivative controller as well as a receding horizon model predictive controller that employs an extended Kalman filter algorithm for predicting future heart motion.