The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
Force Modeling for Needle Insertion Into Soft Tissue
Abstract
The modeling of forces during needle insertion into soft tissue is important for accurate surgical simulation, preoperative planning, and intelligent robotic assistance for percutaneous therapies. We present a force model for needle insertion and experimental procedures for acquiring data from ex vivo tissue to populate that model. Data were collected from bovine livers using a one-degree-of-freedom robot equipped with a load cell and needle attachment. computed tomography imaging was used to segment the needle insertion process into phases identifying different relative velocities between the needle and tissue. The data were measured and modeled in three parts: 1) capsule stiffness, a nonlinear spring model; 2) friction, a modified Karnopp model; and 3) cutting, a constant for a given tissue. In addition, we characterized the effects of needle diameter and tip type on insertion force using a silicone rubber phantom. In comparison to triangular and diamond tips, a bevel tip causes more needle bending and is more easily affected by tissue density variations. Forces for larger diameter needles are higher due to increased cutting and friction forces.
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Cites
Biomechanics: Mechanical Properties of Living Tissues
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Needle insertion modeling and simulation
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Reality-based models for vibration feedback in virtual environments
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Self-citationMeasuring in vivo animal soft tissue properties for haptic modeling in surgical simulation.
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Cited by
Nonholonomic Modeling of Needle Steering
Webster, R. J., Cowan, N. J., Chirikjian, G., & Okamura, A. M. (2006) · Springer Tracts in Advanced Robotics · doi:10.1007/11552246_4 · Cited by 527
Self-citationMicroneedle, bio-microneedle and bio-inspired microneedle: A review
Ma, G., & Wu, C. (2017) · Journal of Controlled Release · doi:10.1016/j.jconrel.2017.02.011 · Cited by 477
A Novel Layer Jamming Mechanism With Tunable Stiffness Capability for Minimally Invasive Surgery
Kim, Y.-J., Cheng, S., Kim, S., & Iagnemma, K. (2013) · IEEE Transactions on Robotics · doi:10.1109/tro.2013.2256313 · Cited by 428
Olatunji, O., Das, D. B., Garland, M. J., Belaid, L., & Donnelly, R. F. (2013) · Journal of Pharmaceutical Sciences · doi:10.1002/jps.23439 · Cited by 277
In Vivo Penetration Mechanics and Mechanical Properties of Mouse Brain Tissue at Micrometer Scales
Sharp, A. A., Ortega, A. M., Restrepo, D., Curran-Everett, D., & Gall, K. (2009) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2008.2003261 · Cited by 157
Metadata
- Authors
- Okamura, A. M., Simone, C., & O'Leary, M. D.
- Venue
- IEEE Transactions on Biomedical Engineering
- Published
- 2004-10
- Volume
- 51
- Issue
- 10
- Pages
- 1707-1716
- ISSN
- 0018-9294 (ISSN-L)
- OpenAlex
- W2109121052
- Cited by
- 830
- References
- 15
- FWCI
- 16.40
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
