Abstract
In current robotic surgery, dexterity is enhanced by microprocessor controlled mechanical wrists which allow motion scaling for reduced gross hand movements and improved performance of micro-scale tasks. The continuing evolution of the technology, including force feedback and virtual immobilization through real-time motion adaptation, will permit complex procedures such as beating heart surgery to be carried out under a static frame-of-reference. In pursuing more adaptive and intelligent robotic designs, the regulatory, ethical and legal barriers imposed on interventional surgical robots have given rise to the need of a tightly integrated control between the operator and the robot when autonomy is considered. This paper outlines the general concept of perceptual docking for robotic control and how it can be used for learning and knowledge acquisition in robotic assisted minimally invasive surgery such that operator specific motor and perceptual/cognitive behaviour is acquired through in situ sensing. A gaze contingent framework is presented in this paper as an example to illustrate how saccadic eye movements and ocular vergence can be used for attention selection, recovering 3D tissue deformation and motor channelling during minimally invasive surgical procedures.
Keywords
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Moore, M.M.: Real-World Applications for Brain-Computer Interface Technology. IEEE Trans. on Neural Systems and Rehabilitation Engineering 11(2), 162–165 (2003)
Wolpaw, J.R., McFarland, D.J.: Control of a Two-Dimensional Movement Signal by a Noninvasive Brain-Computer Interface in Humans. NeuroScience 101(51), 17849–17854 (2004)
Serruya, M.D., Hatsopoulos, N.G., Paninski, L., Fellow, M.R., Donoghue, J.P.: Instant Neural Control of a Movement Signal. Nature 416, 141–142 (2002)
Yoo, S.S., Fairneny, T., Chen, N.K., Choo, S.E., Panych, L.P., Park, H., Lee, S.Y., Jolesz, F.A.: Brain-Computer Interface Using fMRI: Spatial Navigation by Thoughts. Neuroreport 15(10), 1591–1595 (2004)
Franceschini, M.A., Boas, D.A.: Noninvasive Measurement of Neuronal Activity with Near-Infrared Optical Imaging. NeuroImage 21(1), 372–386 (2004)
Coyle, S.M., Ward, T.E., Markham, C.M.: Brain-Computer Interface Using a Simplified Functional Near-Infrared Spectroscopy System. Journal of Neural Eng. 4(3), 219–226 (2007)
Tsubone, T., Muroga, T., Wada, Y.: Application to Robot Control Using Brain Function Measurement by Near-Infrared Spectroscopy. In: Proc. of IEEE Eng. Med. Biol. Soc., pp. 5324–5345 (2007)
Sitaram, R., Zhang, H., Guan, C., Thulasidas, M., Hoshi, Y., Ishikawa, A., Shimizu, K., Birbaumer, N.: Temporal Classification of Multichannel Near-Infrared Spectroscopy Signals of Motor Imagery for Developing a Brain-Computer Interface. Neuroimage 34(4), 1416–1427 (2007)
Leff, D., Koh, P.H., Aggarwal, R., Leong, J., Deligiani, F., Elwell, C., Delpy, D.T., Darzi, A., Yang, G.Z.: Optical Mapping of the Frontal Cortex During a Surgical Knot-Tying Task, a Feasibility Study. In: Medical Imaging Augmented Reality, pp. 140–147 (2006)
Leff, D.R., Leong, J.J., Aggarwal, R., Yang, G.Z., Darzi, A.: Could Variations in Technical Skills Acquisition in Surgery be Explained by Differences in Cortical Plasticity? Annals of Surgery 247(3), 540–543 (2008)
Leff, D.R., Orihuela-Espina, F., Atallah, L., Darzi, A., Yang, G.Z.: Functional Near Infrared Spectroscopy in Novice and Expert Surgeons - a Manifold Embedding Approach. In: Ayache, N., Ourselin, S., Maeder, A. (eds.) MICCAI 2007, Part II. LNCS, vol. 4792, pp. 270–277. Springer, Heidelberg (2007)
Leff, D.R., Elwell, C.E., Orihuela-Espina, F., Atallah, L., Delpy, D.T., Darzi, A.W., Yang, G.Z.: Changes in Prefrontal Cortical Behaviour Depend Upon Familiarity on a Bimanual Co-Ordination Task: an fNIRS Study. Neuroimage 39(2), 805–813 (2008)
Yang, G.Z., Dempere-Marco, L., Hu, X.-P., Rowe, A.: Visual Search: Psychophysical Models and Practical Applications. Image and Vision Computing 20, 291–305 (2002)
Mylonas, G.P., Darzi, A., Yang, G.Z.: Gaze Contingent Depth Recovery and Motion Stabilisation for Minimally Invasive Robotic Surgery. In: Yang, G.-Z., Jiang, T. (eds.) MIAR 2004. LNCS, vol. 3150, pp. 311–319. Springer, Heidelberg (2004)
Mylonas, G.P., Stoyanov, D., Deligianni, F., Darzi, A., Yang, G.-Z.: Gaze-Contingent Soft Tissue Deformation Tracking for Minimally Invasive Robotic Surgery. In: Duncan, J.S., Gerig, G. (eds.) MICCAI 2005. LNCS, vol. 3749, pp. 843–850. Springer, Heidelberg (2005)
Lerotic, M., Chung, A.J., Mylonas, G., Yang, G.-Z.: pq-Space Based Non-Photorealistic Rendering for Augmented Reality. In: Ayache, N., Ourselin, S., Maeder, A. (eds.) MICCAI 2007, Part II. LNCS, vol. 4792, pp. 102–109. Springer, Heidelberg (2007)
Rosenberg, L.B.: Virtual Fixtures: Perceptual Tools for Telerobotic Manipulation. In: Proc. of the IEEE Annual International Symposium on Virtual Reality, pp. 76–82 (1993)
Mylonas, G.P., Kwok, K.-W., Darzi, A., Yang, G.Z.: Gaze-Contingent Motor Channelling and Haptic Constraints for Minimally Invasive Robotic Surgery. In: Proceedings of the 11th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2008, New York (to appear, 2008)
Okamura, A.M.: Methods for Haptic Feedback in Teleoperated Robot-Assisted Surgery. Industrial Robot: An International Journal 31(6), 499–508 (2004)
Mendoza, C., Laugier, C.: Tissue Cutting Using Finite Elements and Force Feedback. In: Proc. of International Symposium on Surgery Simulation and Soft Tissue Modeling, pp. 175–182 (2003)
Crouch, J.R., Schneider, C.M., Wainer, J., Okamura, A.M.: A Velocity-Dependent Model for Needle Insertion in Soft Tissue. In: Duncan, J.S., Gerig, G. (eds.) MICCAI 2005. LNCS, vol. 3750, pp. 624–632. Springer, Heidelberg (2005)
Heverly, M., Dupont, P., Triedman, J.: Trajectory Optimization for Dynamic Needle Insertion. In: Proc. of the 2005 IEEE International Conf. on Robotics and Automation, pp. 1646–1651 (2005)
Kennedy, C.W., Hu, T., Desai, J.P., Wechsler, A.S., Kresh, J.Y.: A Novel Approach to Robotic Cardiac Surgery Using Haptics and Vision. Cardiovascular Engineering: An International Journal 2(1), 15–21 (2002)
Tholey, G., Desai, J.P.: A General Purpose 7 DOF Haptic Device: Applications Towards Robot-Assisted Surgery. IEEE/ASME Trans. on Mechatronics 12(6), 662–669 (2007)
Unger, B., Hollis, R., Klatzky, R.: JND Analysis of Texture Roughness Perception Using a Magnetic Levitation Haptic Device. In: Proc. Of the 2nd Joint Eurohaptics Conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, pp. 9–15 (2007)
Saddik, E.: The Potential of Haptics Technologies. IEEE Instrumentation and Measurement Magazine 10(1), 10–17 (2007)
Lin, M., Salisbury, K.: Haptic Rendering-Beyond Visual Computing. IEEE Computer Graphics and Applications 24(2), 22–23 (2004)
Orozco, M., Asfaw, Y., Shirmohammadi, S.S., Adler, A., Saddik, A.E.: Haptic-Based Biometrics: A Feasibility Study. In: Proc. of the Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, pp. 265–271 (2006)
Tsagarakis, N.G., Petrone, M., Testi, D., Mayoral, R., Zannoni, C., Viceconti, M., Clapworthy, G.J., Gray, J.O., Caldwell, D.G.: Pre-Operative Planning for Total Hip Arthroplasty Using a Haptic Enabled Multimodal Interface and Framework. IEEE Trans. of Multimedia and Visualization: Special issue in Haptics 13(3), 40–48 (2006)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Yang, GZ., Mylonas, G.P., Kwok, KW., Chung, A. (2008). Perceptual Docking for Robotic Control. In: Dohi, T., Sakuma, I., Liao, H. (eds) Medical Imaging and Augmented Reality. MIAR 2008. Lecture Notes in Computer Science, vol 5128. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79982-5_3
Download citation
DOI: https://doi.org/10.1007/978-3-540-79982-5_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-79981-8
Online ISBN: 978-3-540-79982-5
eBook Packages: Computer ScienceComputer Science (R0)