Triaxial MRI-Compatible Fiber-optic Force Sensor

Magnetic resonance imaging (MRI) has gained popularity over standard imaging modalities like ultrasound and computed tomography because of its ability to provide excellent soft-tissue contrast. However, due to the working principle of MRI, a number of conventional force sensors are not compatible. One popular solution is to develop a fiber-optic force sensor. However, the measurements along the principal axes of a number of these force sensors are highly cross-coupled. One of the objectives of this paper is to minimize this coupling effect. In addition, this paper describes the design of elastic frame structures that are obtained systematically using topology optimization techniques for the maximization of sensor resolution and sensor bandwidth. Through the topology optimization approach, we ensure that the frames are linked from the input to output. The elastic frame structures are then fabricated using polymers materials, such as ABS and Delrin®, as they are ideal materials for use in the MRI environment. However, the hysteresis effect seen in the displacement-load graph of plastic materials is known to affect the accuracy. Hence, this paper also proposes modeling and addressing this hysteretic effect by the use of Prandtl-Ishlinskii play operators. Finally, experiments are conducted to evaluate the sensor's performance, as well as its compatibility in MRI under continuous imaging.

[1]  Bo Yang,et al.  Design and development of a 3-axis MRI-compatible force sensor , 2010, 2010 IEEE International Conference on Robotics and Automation.

[2]  Etienne Burdet,et al.  Design of a simple MRI/fMRI compatible force/torque sensor , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

[3]  Hannes Bleuler,et al.  2-DOF fMRI-Compatible Haptic Interface for Bimanual Motor Tasks with Grip/Load Force Measurement , 2008, The Sense of Touch and its Rendering.

[4]  K. Leong,et al.  Rapid Prototyping: Principles and Applications (with Companion CD-ROM) , 2003 .

[5]  G. K. Ananthasuresh,et al.  A Comparative Study of the Formulations and Benchmark Problems for the Topology Optimization of Compliant Mechanisms , 2009 .

[6]  U-Xuan Tan,et al.  Feedforward Controller of Ill-Conditioned Hysteresis Using Singularity-Free Prandtl–Ishlinskii Model , 2009, IEEE/ASME Transactions on Mechatronics.

[7]  Mitsunori Tada,et al.  Development of an optical 2-axis force sensor usable in MRI environments , 2002, Proceedings of IEEE Sensors.

[8]  O. Sigmund.  Morphology-based black and white filters for topology optimization , 2007 .

[9]  Kaspar Althoefer,et al.  Novel design of a 3-axis optical fiber force sensor for applications in magnetic resonance environments , 2009, 2009 IEEE International Conference on Robotics and Automation.

[10]  M. Tada,et al.  High-precision MRI-compatible force sensor with parallel plate structure , 2008, 2008 2nd IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics.

[11]  G. K. Ananthasuresh,et al.  On an optimal property of compliant topologies , 2000 .

[12]  Klaus Kuhnen,et al.  Modeling, Identification and Compensation of Complex Hysteretic Nonlinearities: A Modified Prandtl - Ishlinskii Approach , 2003, Eur. J. Control.

[13]  M. Omizo,et al.  Modeling , 1983, Encyclopedic Dictionary of Archaeology.

[14]  R. Gassert,et al.  MRI/fMRI-compatible robotic system with force feedback for interaction with human motion , 2006, IEEE/ASME Transactions on Mechatronics.

[15]  G. K. Ananthasuresh,et al.  Design of Distributed Compliant Mechanisms , 2003 .

[16]  Leong Kah Fai,et al.  Rapid Prototyping: Principles and Applications in Manufacturing , 2003 .

[17]  Kaspar Althoefer,et al.  Mathematical Modeling of Intensity-Modulated Bent-Tip Optical Fiber Displacement Sensors , 2010, IEEE Transactions on Instrumentation and Measurement.

[18]  Jaydev P. Desai,et al.  A biplanar fluoroscopic approach for the measurement, modeling, and simulation of needle and soft-tissue interaction , 2007, Medical Image Anal..

[19]  Antonio Bicchi,et al.  The Sense of Touch and its Rendering - Progress in Haptics Research , 2008 .

[20]  U-Xuan Tan,et al.  Tracking Control of Hysteretic Piezoelectric Actuator using Adaptive Rate-Dependent Controller. , 2009, Sensors and actuators. A, Physical.

[21]  Takeo Kanade,et al.  An MR-Compatible Optical Force Sensor for Human Function Modeling , 2004, MICCAI.

[22]  Jaydev P. Desai,et al.  Towards a teleoperated needle driver robot with haptic feedback for RFA of breast tumors under continuous MRI , 2009, Medical Image Anal..

[23]  Jaydev P. Desai,et al.  Towards a needle driver robot for radiofrequency ablation of tumors under continuous MRI , 2008, 2008 IEEE International Conference on Robotics and Automation.

[24]  Jian S. Dai,et al.  Analysis of Force Distribution in Grasps Using Augmentation , 1996 .

[25]  Jian S. Dai,et al.  A six-component contact force measurement device based on the Stewart platform , 2000 .

[26]  Ole Sigmund,et al.  On the Design of Compliant Mechanisms Using Topology Optimization , 1997 .

[27]  Tsukasa Ogasawara,et al.  An Optical 6-Axis Force Sensor for Brain Function Analysis using fMRI , 2004 .

[28]  Zion Tsz Ho Tse,et al.  The case for MR‐compatible robotics: a review of the state of the art , 2008, The international journal of medical robotics + computer assisted surgery : MRCAS.

[29]  Mary Frecker,et al.  Topological synthesis of compliant mechanisms using multi-criteria optimization , 1997 .

[30]  Kaspar Althoefer,et al.  Optical fiber sensor for soft tissue investigation during minimally invasive surgery , 2008, 2008 IEEE International Conference on Robotics and Automation.

[31]  E. Burdet,et al.  Sensors for Applications in Magnetic Resonance Environments , 2008, IEEE/ASME Transactions on Mechatronics.