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Methodology for the selection of a smart material as actuator in neurosurgical robotics
| Назва | Methodology for the selection of a smart material as actuator in neurosurgical robotics |
| Назва англійською | Methodology for the selection of a smart material as actuator in neurosurgical robotics |
| Автори | Dimitri Gouot; Frédéric Chapelle; Gérard Granet; Jean-Jacques Lemaire; Yuri Lapusta |
| Принадлежність | Université Clermont Auvergne, CNRS, SIGMA Clermont, Institut Pascal,F-63000 Clermont-Ferrand, France
Université Clermont Auvergne, CHU Clermont-Ferrand, CNRS, SIGMA Clermont, Institut Pascal, F-63000 Clermont-Ferrand, France |
| Бібліографічний опис | Methodology for the selection of a smart material as actuator in neurosurgical robotics / Dimitri Gouot; Frédéric Chapelle; Gérard Granet; Jean-Jacques Lemaire; Yuri Lapusta // Scientific Journal of TNTU. — Tern.: TNTU, 2020. — Vol 100. — No 4. — P. 5–10. |
| Bibliographic description: | Gouot D.; Chapelle F.; Granet G.; Lemaire J.-J.; Lapusta Yu. (2020) Methodology for the selection of a smart material as actuator in neurosurgical robotics. Scientific Journal of TNTU (Tern.), vol 100, no 4, pp. 5–10. |
| УДК |
339 |
| Ключові слова |
smart materials, neurosurgical robotics, specifications. |
|
In this article we define the criteria and present the methodology to choose a smart material in order to actuate a soft neurosurgery robot. These criteria are defined with the experience of a neurosurgeon. |
| ISSN: | 2522-4433 |
| Перелік літератури |
1. Alric M., Chapelle F., Lemaire J-J., Gogu G. Potential applications of medical and non-medical robots for neurosurgical applications. Minimally Invasive Therapy & Allied Technologies. 2009.18 (4). Р. 193–216.
2. Martin C., Chapelle F., Lemaire J-J., Gogu G. Neurosurgical robot design and interactive motion planning for resection task. In: Proc of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). St. Louis, USA, 2009. Р. 4505–4510.
3. Li Q. H., Zamorano L., Pandya A., Perez R. The Application Accuracy of the NeuroMate Robot – A Quantitative Comparison with Frameless and Frame-Based Surgical Localization Systems. Computer Aided Surgery. 2002. 7. P. 90–98.
4. Frasson L., Ko S. Y., Turner A., Parittotokkaporn T., Vincent J. F., Rodriguez y Baena F. STING: a soft-tissue intervention and neurosurgical guide to access deep brain lesions through curved trajectories. Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine. 2010. 224 (6). Р. 775–788.
5. Chikhaoui M. T., Benouhiba A., Rougeot P., Rabenorosoa K., Ouisse M., Andreff N. Developments and Control of Biocompatible Conducting Polymer for Intracorporeal Continuum Robots. Annals of Biomedical Engineering. 2018. 46 (10). Р. 1511–21.
6. Petruska A. J., Ruetz F., Hong A., Regli L., Sürücü O., Zemmar A., et al. Magnetic needle guidance for neurosurgery: Initial design and proof of concept. In: Proc. of the IEEE International Conference on Robotics and Automation (ICRA). Stockholm, Sweden. 2016. Р. 4392–7.
7. Ryu S. C., Quek Z. F., Koh J-S., Renaud P., Black R. J., Moslehi B., et al. Design of an optically controlled MR-compatible active needle. IEEE Transactions on Robotics. 2015. 31 (1). Р. 1–11.
8. Alric M. Conception et modélisation modulaire d’un robot bio-inspiré extensible pour l’accès aux tumeurs dans le cerveau. PhD thesis, Université Blaise Pascal-Clermont-Ferrand II, 2009.
9. Lee K. M., Koerner H., Vaia R. A., Bunning T. J., White T. J. Light-activated shape memory of glassy, azobenzene liquid crystalline polymer networks. Soft Matter. 2011. 7 (9). Р. 4318.
10. Edelmann J., Petruska A. J., Nelson B. J. Magnetic control of continuum devices. The International Journal of Robotics Research. 2017. 36 (1). Р. 68‑85.
11. Feng J., Xuan S., Lv Z., Pei L., Zhang Q., Gong X. Magnetic-Field-Induced Deformation Analysis of Magnetoactive Elastomer Film by Means of DIC, LDV, and FEM. Industrial & Engineering Chemistry Research. 2018. 57 (9). 3246–54.
12. Feng J., Xuan S., Ding L., Gong X. Magnetoactive elastomer/PVDF composite film based magnetically controllable actuator with real-time deformation feedback property. Composites Part A: Applied Science and Manufacturing. 2017. 103. Р. 25–34.
13. Wang W., Yao Z., Chen J. C., Fang J. Composite elastic magnet films with hard magnetic feature. Journal of Micromechanics and microengineering. 2004. 14 (10). Р. 1321.
14. Vartholomeos P., Qin L., Dupont P. E. MRI-Powered Actuators for Robotic Interventions. In: Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). San Francisco, USA; 2011. Р. 4508–4515.
15. Carrico J. D., Traeden N. W., Aureli M., Leang K. K. Fused filament 3D printing of ionic polymer-metal composites (IPMCs). Smart Materials and Structures. 2015. 24 (12). 125021.
16. Shahinpoor M., Kim K. J. Ionic polymer–metal composites: III. Modeling and simulation as biomimetic sensors, actuators, transducers, and artificial muscles. Smart Materials and Structures. 2004. 13 (6). Р. 1362–88.
17. Shahinpoor M., Kim K. J. Ionic polymer–metal composites: IV. Industrial and medical applications. Smart Materials and Structures. 2005. 14 (1). Р. 197–214.
18. Carrico J. D., Traeden N. W., Aureli M., Leang K. K. Fused Filament Additive Manufacturing of Ionic Polymer-Metal Composite Soft Active 3D Structures. In: Volume 1: Development and Characterization of Multifunctional Materials; Mechanics and Behavior of Active Materials; Modeling, Simulation and Control of Adaptive Systems. Colorado Springs, USA: ASME; 2015. V001T01A004.
19. Carrico J. D., Tyler T., Leang K. K. A comprehensive review of select smart polymeric and gel actuators for soft mechatronics and robotics applications: fundamentals, freeform fabrication, and motion control. International Journal of Smart and Nano Materials. 2017. 8 (4). Р. 144–213. |
| References: |
1. Alric M., Chapelle F., Lemaire J-J., Gogu G. Potential applications of medical and non-medical robots for neurosurgical applications. Minimally Invasive Therapy & Allied Technologies. 2009.18 (4). Р. 193–216.
2. Martin C., Chapelle F., Lemaire J-J., Gogu G. Neurosurgical robot design and interactive motion planning for resection task. In: Proc of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). St. Louis, USA, 2009. Р. 4505–4510.
3. Li Q. H., Zamorano L., Pandya A., Perez R. The Application Accuracy of the NeuroMate Robot – A Quantitative Comparison with Frameless and Frame-Based Surgical Localization Systems. Computer Aided Surgery. 2002. 7. P. 90–98.
4. Frasson L., Ko S. Y., Turner A., Parittotokkaporn T., Vincent J. F., Rodriguez y Baena F. STING: a soft-tissue intervention and neurosurgical guide to access deep brain lesions through curved trajectories. Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine. 2010. 224 (6). Р. 775–788.
5. Chikhaoui M. T., Benouhiba A., Rougeot P., Rabenorosoa K., Ouisse M., Andreff N. Developments and Control of Biocompatible Conducting Polymer for Intracorporeal Continuum Robots. Annals of Biomedical Engineering. 2018. 46 (10). Р. 1511–21.
6. Petruska A. J., Ruetz F., Hong A., Regli L., Sürücü O., Zemmar A., et al. Magnetic needle guidance for neurosurgery: Initial design and proof of concept. In: Proc. of the IEEE International Conference on Robotics and Automation (ICRA). Stockholm, Sweden. 2016. Р. 4392–7.
7. Ryu S. C., Quek Z. F., Koh J-S., Renaud P., Black R. J., Moslehi B., et al. Design of an optically controlled MR-compatible active needle. IEEE Transactions on Robotics. 2015. 31 (1). Р. 1–11.
8. Alric M. Conception et modélisation modulaire d’un robot bio-inspiré extensible pour l’accès aux tumeurs dans le cerveau. PhD thesis, Université Blaise Pascal-Clermont-Ferrand II, 2009.
9. Lee K. M., Koerner H., Vaia R. A., Bunning T. J., White T. J. Light-activated shape memory of glassy, azobenzene liquid crystalline polymer networks. Soft Matter. 2011. 7 (9). Р. 4318.
10. Edelmann J., Petruska A. J., Nelson B. J. Magnetic control of continuum devices. The International Journal of Robotics Research. 2017. 36 (1). Р. 68‑85.
11. Feng J., Xuan S., Lv Z., Pei L., Zhang Q., Gong X. Magnetic-Field-Induced Deformation Analysis of Magnetoactive Elastomer Film by Means of DIC, LDV, and FEM. Industrial & Engineering Chemistry Research. 2018. 57 (9). 3246–54.
12. Feng J., Xuan S., Ding L., Gong X. Magnetoactive elastomer/PVDF composite film based magnetically controllable actuator with real-time deformation feedback property. Composites Part A: Applied Science and Manufacturing. 2017. 103. Р. 25–34.
13. Wang W., Yao Z., Chen J. C., Fang J. Composite elastic magnet films with hard magnetic feature. Journal of Micromechanics and microengineering. 2004. 14 (10). Р. 1321.
14. Vartholomeos P., Qin L., Dupont P. E. MRI-Powered Actuators for Robotic Interventions. In: Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). San Francisco, USA; 2011. Р. 4508–4515.
15. Carrico J. D., Traeden N. W., Aureli M., Leang K. K. Fused filament 3D printing of ionic polymer-metal composites (IPMCs). Smart Materials and Structures. 2015. 24 (12). 125021.
16. Shahinpoor M., Kim K. J. Ionic polymer–metal composites: III. Modeling and simulation as biomimetic sensors, actuators, transducers, and artificial muscles. Smart Materials and Structures. 2004. 13 (6). Р. 1362–88.
17. Shahinpoor M., Kim K. J. Ionic polymer–metal composites: IV. Industrial and medical applications. Smart Materials and Structures. 2005. 14 (1). Р. 197–214.
18. Carrico J. D., Traeden N. W., Aureli M., Leang K. K. Fused Filament Additive Manufacturing of Ionic Polymer-Metal Composite Soft Active 3D Structures. In: Volume 1: Development and Characterization of Multifunctional Materials; Mechanics and Behavior of Active Materials; Modeling, Simulation and Control of Adaptive Systems. Colorado Springs, USA: ASME; 2015. V001T01A004.
19. Carrico J. D., Tyler T., Leang K. K. A comprehensive review of select smart polymeric and gel actuators for soft mechatronics and robotics applications: fundamentals, freeform fabrication, and motion control. International Journal of Smart and Nano Materials. 2017. 8 (4). Р. 144–213. |
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