Hostname: page-component-586b7cd67f-dsjbd Total loading time: 0 Render date: 2024-11-22T14:59:45.398Z Has data issue: false hasContentIssue false

Sliding mode control of a shape memory alloy actuated active flexible needle

Published online by Cambridge University Press:  07 May 2018

Felix Orlando Maria Joseph*
Affiliation:
Department of Radiation Oncology, Case Western Reserve University, Cleveland, OH 44106, USA Department of Electrical Engineering, IIT Roorkee, Roorkee, Uttarakhand 247667, India
Tarun Podder*
Affiliation:
Department of Radiation Oncology, Case Western Reserve University, Cleveland, OH 44106, USA
*
*Corresponding author. E-mail: [email protected]

Summary

In medical interventional procedures such as brachytherapy, biopsy and radio-frequency ablation, precise tracking through the preplanned desired trajectory is very essential. This important requirement is critical due to two major reasons: anatomical obstacle avoidance and accurate targeting for avoiding undesired radioactive dose exposure or damage to neighboring tissue and critical organs. Therefore, a precise control of the needling device in the unstructured environment in the presence of external disturbance is required to achieve accurate target reaching in clinical applications. In this paper, a shape memory alloy actuated active flexible needle controlled by an adaptive sliding mode controller is presented. The trajectory tracking performance of the needle is tested while having its actual movement in an artificial tissue phantom by giving various input reference trajectories such as multi-step and sinusoidal. Performance of the adaptive sliding mode controller is compared with that of the proportional, integral and derivative controller and is proved to be the effective method in the presence of the external disturbances.

Type
Articles
Copyright
Copyright © Cambridge University Press 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. Abolhassani, N., Patel, R. and Moallem, M., “Needle insertion into soft tissue: A survey,” Med. Eng. Phys. 29 (4), 413431 (2007).CrossRefGoogle ScholarPubMed
2. Webster, R. J. III, Okamura, A. M. and Cowan, N. J. “Towards Active Cannulas: Miniature Snake-Like Surgical Robots,” Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2006), Beijing, China, (Oct. 9–15, 2006) pp. 2857–2863.CrossRefGoogle Scholar
3. Swaney, P. J., Burgner, J., Webster, R. J. III and Alterovitz, R., “A flexure-based steerable needle: High curvature with reduced tissue damage,” IEEE Trans. Biomed. Eng. 60 (4), 906909 (2013).CrossRefGoogle ScholarPubMed
4. Okamura, A. M., Simone, C. and O'Leavy, M. D., “Force modeling for needle insertion into soft tissue,” IEEE Trans. Biomed. Eng. 51 (10), 17071716 (2004).CrossRefGoogle ScholarPubMed
5. DiMaio, S. P. and Salcudean, S. E., “Interactive simulation of needle insertion models,” IEEE Trans. Robot. 52 (7), 11671179 (2005).Google Scholar
6. Goksel, O., Salcudean, S. E. and DiMaio, S. P., “3D simulation of needle-tissue interaction with application of prostate brachytherapy, Comp. Aid. Sur. 11 (6), 279288 (2006).Google Scholar
7. Gao, D., Lei, Y., Lian, B. and Yao, B., “Modeling and simulation of flexible needle insertion into soft tissue using modified local constraints,” J. Manuf. Sci. Eng. 138 (12), 1210112112 (2016).Google Scholar
8. Glozman, D. and Shoham, M., “Image-guided robotic flexible needle steering,” IEEE Trans. Biomed. Eng. 23, 459467 (2007).Google Scholar
9. Barnett, A. C., Lee, Y. S. and Moore, J. Z., “Fracture mechanics model of needle cutting tissue,” J. Manuf. Sci. Eng. 138, 011005011011 (2016).CrossRefGoogle Scholar
10. Reed, K. B., Kallem, V., Alterovitz, R., Goldberg, K., Okamura, A. and Cowan, N. J., “Integrated Planning and Image-guided Control for Planar Needle Steering,” Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, (2008) pp. 819–824.Google Scholar
11. Reed, K. B., Majewik, A., Kallem, V., Alterovitz, R., Goldberg, K., Cowan, N. J. and Okamura, A. M., “Robot-assisted needle steering,” IEEE Robot. Autom. Mag. 18 (4), 3546 (2011).Google Scholar
12. Alterovitz, R. and Goldberg, K., “The Stochastic Motion Roadmap: A Sampling Framework for Planning with Markov Motion Uncertainty,” Proceedings of the Robotics: Science and Systems Conference, Atlanta, GA, USA (2007) pp. 1–8.Google Scholar
13. Kallem, V. and Cowan, N. J., “Image guidance of flexible tip-steerable needles,” IEEE Trans. Robot. 25 (1), 191196 (2009).Google Scholar
14. Swensen, J. P. and Cowan, N. J., “Torsional Dynamics of Compensation Enhances Robotic Control of Tip-steerable Needles,” Proceedings of the IEEE International Conference on Robotics and Automation, Minnesota, USA (2012) pp. 1601–1606.Google Scholar
15. Wood, N. A., Shahrour, K., Ost, M. C. and Riviere, C. N., “Needle Steering System using Duty-cycled Rotation for Percutaneous Kidney Access,” Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society (2010) pp. 5432–5435.Google Scholar
16. Wood, N. A., Shehrour, K., Ost, M. C. and Riviere, C. N. “Closed-loop Control of Needle Steering for Percutaneous Kidney Access,” Proceedings of the In ICRA Workshop on Snakes, Worms and Catheters: Continuum and Serpentine Robots for Minimally Invasive Surgery, 4 (2010) pp. 48–50.Google Scholar
17. Ko, S. Y. and Rodriguez y Baena, F., “Trajectory following for a flexible probe with state/input constraints: An approach based on model predictive control,” Robot Autonomous Syst. 60 (4), 509521 (2012).CrossRefGoogle Scholar
18. Bui, V. K., Park, S., Park, J. and Ko, S. Y., “A novel curvature-controllable steerable needle for percutaneous intervention,” J. Eng. Med. 230 (8), 727738 (2016).Google Scholar
19. Hauser, K., Alterovitz, R., Chentanez, N., Okamura, A. M. and Goldberg, K., “Feedback Control for Steering Needles Through 3D Deformable Tissue using Helical Paths,” Proceedings of the in Proceedings on the Robotics: Science and Systems Conference, Seattle, USA (2009) pp. 1–8.Google Scholar
20. Abayazid, M., Roesthais, R. J., Reilink, R. and Misra, S., “Integrating deflection models and image feedback for real-time flexible needle steering,” IEEE Trans. Robot. 29 (2), 542553 (2013).CrossRefGoogle Scholar
21. Patil, S., Burgner, J., Webster, R. J. III, and Alterovitz, R., “Needle steering in 3D via rapid replanning,” IEEE Trans. Robot. 30 (4), 853864 (2014).Google Scholar
22. Podder, T. K., Hutapea, P., Darvish, K., Dicker, A. and Yu, Y., “Smart Needling System for Fully Conformal Radiation Dose Delivery in Treating Prostate Cancer,” Proceedings of the ASME 2010 Conference on Smart Materials, Adaptive Structures and Intelligent Systems(SMASIS), Philadelphia, PA (Sep. 28–Oct. 1) pp. 1–4.Google Scholar
23. Podder, T. K., Dicker, A. P., Hutapea, P., Darvish, K. and Yu, Y., “A novel curvilinear approach for prostate seed implant,” J. Med. Phys. 39 (4), 18871892 (2012).CrossRefGoogle Scholar
24. Stock, R. G., Stone, N. N., Lo, Y. C., Malhoda, N., Kao, J. and DeWyngaert, J. K., “Postimplant dosimetry for 125I prostate implants: Definitions and factors affecting outcome,” Int. J. Radiat. Oncol. Biol. Phys. 48 (3), 899906 (2000).Google Scholar
25. Webster, R. J., Romano, J. M. and Cowan, N. J., “Mechanics of precurved-tube continuum robots,” IEEE Trans. Robot. 25 (1), 6778 (2009).CrossRefGoogle Scholar
26. Sears, P. and Dupont, P., “A Steerable Needle Technology using Curved Concentric Tubes,” Proceedings of the 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Beijing, China (2006) pp. 2850–1856.Google Scholar
27. Reed, K. B., Okamura, A. M. and Cowan, N. J., “Modeling and control of needles with torsional friction,” IEEE Trans. Biomed. Eng. 56 (12), 29052916 (2009).Google Scholar
28. Reed, K. B., Okamura, A. M. and Cowan, N. J., “Controlling a Robotically Steered Needle in the Presence of Torsional Friction,” Proceedings of the IEEE International Conference on Robotics and Automation (2009) pp. 3476–3481.Google Scholar
29. Swensen, J. P., Lin, M., Okamura, A. M. and Cowan, N. J., “Torsional dynamics of steerable needles: Modeling and fluoroscopic guidance,” IEEE Trans. Biomed. Eng. 61 (11), 27072717 (2014).Google Scholar
30. Burdette, E. C., Rucker, D. C., Prakash, P., Diederich, C. J., Croom, J. M., Clarke, C., Stolka, P., Juang, T., Boctor, E. M. and Webster, R. J., “The ACUSITT Ultrasonic Ablator: The First Steerable Needle with an Integrated Interventional Tool,” Proceedings of SPIE, Med, Imag. Ultrason. Imag., Tomogr., Ther., 7629 (2010) pp. 76290V-1–79641I-10.Google Scholar
31. Burgner, J., Swaney, P. J., Bruns, T. L., Clark, M. S., Rucker, D. C., Burdette, E. C. and Webster, R. J., “An autoclavable steerable cannula manual deployment device: Design and accuracy analysis,” J. Med. Devices 6 (4), 041007 (2012).Google Scholar
32. Levy, W. J. and Oro, J. J., “Curved biopsy needle for stereotactic surgery: A technical note,” Neurosurgery 15 (1), 8285 (1984).Google Scholar
33. Furusho, J., Ono, T., Chiba, Y. and Horio, H., “Development of a Curved Multi-Tube (CMT) Catheter for Percutaneous Umbilical Blood Sampling and Control Methods of CMT Catheters for Solid Organs,” Proceedings of the IEEE Int. Conf. Mech. Autom., (1–4, 2005) pp. 410–415.Google Scholar
34. Jelinek, F., Pessers, R. and Breedveld, P., “DragonFlex smart steerable laparoscopic instrument,” J. Med. Devices 8 (1), 015001015009 (2014).Google Scholar
35. Clogenson, H. C. M., Dankelman, J. and Van den dobbelsteen, J. J., “Steerable guidewire for magnetic resonance guided endovascular interventions,” J. Med. Devices 8 (1), 021002021007 (2014).Google Scholar
36. Henken, K., Van gerwen, D., Dankelman, J. and van den dobbelsteen, J. J., “Steerable guidewire for magnetic resonance guided endovascular interventions,” Minimally Invasive Ther. 21 (6) 408414 (2014).Google Scholar
37. Adebar, T. K., Greer, J. D., Laeseke, P. F., Hwang, G. L. and Okamura, A. M., “Methods for improving the curvature of steerable needles in biological tissues,” IEEE Trans. Biomed. Eng. 63 (6), 11671177 (2016).CrossRefGoogle Scholar
38. Scali, M., Pusch, T. P., Breedveld, P. and Dodou, D., “Needle-like instrument for steering through solid organs: A review on the scientific and patent literature,” Proc. Inst. Mech. Eng. H 231 (3), 250265 (2017).Google Scholar
40. Yamada, A., Naka, S., Nitta, N., Morikawa, S. and Tani, T., “A loop-shaped flexible mechanism for robotic needle steering,” IEEE Robot. Autom. Lett. 3 (2), 648655 (2018).Google Scholar
41. Ryu, S. C., Quek, Z. F., Renaud, P., Black, R. J., Moslehi, B., Daniel, B. L., Cho, K. J. and Cutkosky, M. R., “Design of an optically controlled MR-compatible active needle,” IEEE Trans. Robot. 31 (1), 111 (2015).CrossRefGoogle ScholarPubMed
42. Kohn, B., Honarvar, M. and Hutapea, P., “Design optimization study of a shape memory alloy active needle for biomedical applications,” Med. Eng. Phys. 37 (5), 469477 (2015).Google Scholar
43. Konh, B., Honarvar, M. and Hutapea, P., “Application of SMA wire for an active surgical needle,” ASME Paper No. SMASIS2013-3142 (2013).Google Scholar
44. Konh, B., Datla, N. V. and Hutapea, P., “Feasibility of shape memory alloy wire actuation for an active steerable cannula,” J. Med. Device. 9 (3), 021002-021002-11 (2015).Google Scholar
45. Datla, N. V., Kohn, B., Honarvar, M., Podder, T. K., Dicker, A. P., Yu, Y. and Hutapea, P., “A model to predict deflection of bevel-tipped active needle advancing in soft tissue,” Med. Eng. Phys. 36, 285293 (2014).CrossRefGoogle Scholar
46. Datla, N. V., Koo, J., Choi, D., Kohn, B., Nguyen, T. M., Podder, T. K., Darvish, K., Dicker, A. P., Yu, Y. and Hutapea, P., “Polyacrylamide phantom for needle-tissue interaction studies with active needles,” Med. Eng. Phys., 36, 140145 (2014).Google Scholar
47. Ayvali, E., Liang, C. P., Ho, M., Chen, Y. and Desai, J. P., “Towards a discretely actuated steerable cannula for diagnostic and therapeutic procedures,” Int. J. Robot. Res. 31 (5), 588603 (2012).Google Scholar
48. Ruiz, B., Hutapea, P., Darvish, K., Dicker, A., Yu, Y. and Podder, T. K., “SMA Actuated Flexible Needle Control using EM Sensor Feedback for Prostate Brachytherapy,” IEEE-International Conference on Robotics and Automation, Needle Steering Workshop. http://www.cs.cmu.edu/~surgmech/NeedleWorkshop/posters/ruiz.html.Google Scholar
49. Ko, S. Y., Frasson, L. and Baena, F. R., “Closed-loop planar motion control of a steerable probe with a “programmable bevel” inspired by nature,” IEEE Trans. Robot. 27 (5), 970983 (2011).Google Scholar
50. Xu, K., Zhao, J. and Zheng, X., “Configuration comparison among kinematically optimized continuum manipulators for robotic surgeries through a single access point,” Robotica 33, 20252044 (2015).Google Scholar
51. Maria Joseph, F., Kumar, M., Franz, K., Hutapea, P., Dicker, A. D., Zhao, Y. Z., Yu, Y. and Podder, T., “Control of shape memory alloy actuated flexible needle using multimodal sensory feedbacks,” J Autom. Control Eng. 3 (5), 428434 (2014).Google Scholar
52. Maria Joseph, F., Franz, K., Luan, Y., Zhao, Y. L., Datla, N. V., Hutapea, P., Dicker, A., Yu, Y. and Podder, T., “Development of a Coordinated Controller for Robot-assisted Shape Memory Alloy Actuated Needle for Prostate Brachytherapy,” Proceedings of the 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Chicago, US, (Aug. 26–30, 2014) pp. 357–360.Google Scholar
53. Maria Joseph, F., Kumar, M., Hutapea, P., Dicker, A., Yu, Y. and Podder, T., “Development of self-actuating flexible needle system for surgical procedures,” J. Med. Devices 9, 020945:1–2 (2015).Google Scholar
54. Maria Joseph, F., Kumar, M., Hutapea, P., Dicker, A., Yu, Y. and Podder, T., “Closed Loop Control of a Robot Assisted Smart Flexible Needle for Percutaneous Intervention,” Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Milan, Italy (2015) pp. 3663–3666.Google Scholar
55. Maria Joseph, F., Hans, S., Singhal, A., Yadav, A., Gupta, A., Malhotra, A. and Singh, P. S., “Inverse Kinematic Control of a Smart Active Needle for Percutaneous Intervention,” Proceedings of the IEEE Region 10 Conference (TENCON), 2017, pp. 1159–1164.Google Scholar
56. Van de Berg, N. J., Dankelman, J. and Van den Dobbelsteen, J. J., “Design of an actively controlled steerable needle with tendon actuation and FBG-based shape sensing,” Med. Eng. Phys. 37, 617622 (2015).Google Scholar
57. Rucker, D. C., Das, J., Gilbert, H. B., Swaney, P. J., Miga, M. I., Sarkar, N. and Webster, R. J. III, “Sliding mode control of steerable needles,” IEEE Trans. Robot. 29 (5), 12891299 (2013).Google Scholar
58. Kuo, T., Huang, Y. J., Chen, C. Y. and Chang, C. H., “Adaptive sliding mode control with PID tuning for uncertain systems,” Eng. Lett. 16 (3), EL_16_3_06 (2006).Google Scholar
59. Tai, N. T. and Ahn, K. K., “Adaptive proportional-integral-derivative tuning sliding mode control for a shape memory alloy actuator,” Smart Mater. Structures 20, 113 (2011).CrossRefGoogle Scholar
61. ATI Industrial Automation, Nano17, 6-axis Force/Torque Sensor, ATI Industrial Automation Inc., Apex, NC, 2008. [Online]. Available: http://www.ati-ia.com/products/ft/ft_models.aspx?id=Nano17.Google Scholar