Skip to main content
Log in

Identification of tissue types and boundaries with a fiber optic force sensor

  • Research Paper
  • Special Focus on Robot Sensing and Dexterous Operation
  • Published:
Science China Information Sciences Aims and scope Submit manuscript

Abstract

The absence of tactile force information at the tip of a medical instrument makes precise minimally invasive surgery difficult and is prone to resulting in serious outcomes. In this paper, a fiber optic force sensor is fabricated based on Fabry-Pérot interferometry and integrated with a puncture needle. The force sensor is attached to the needle tip, where interactive force arises as it inserts into soft tissue. Needle insertion experiments have been conducted on ex vivo swine liver and belly with the calibrated force sensor. Using wavelet transform method, the acquired force data are analyzed and used to identify layered tissue types and boundaries. We found that the force amplitudes are not always identical, but the patterns of forces are almost the same, which enables us to identify layered tissues and to realize a safe needle insertion procedure under robot control.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Huo B, Zhao X, Han J, et al. Motion planning for flexible needle in multilayer tissue environment with obstacles. In: Proceesings of the IEEE International Conference on Systems, Man, and Cybernetics, Seoul, 2012. 3292–3297

    Google Scholar 

  2. Aghakhani N, Geravand M, Shahriari N, et al. Task control with remote center of motion constraint for minimally invasive robotic surgery. In: Proceedings of the IEEE International Conference on Robotics and Automation, Karlsruhe, 2013. 5807–5812

    Google Scholar 

  3. Nillahoot N, Suthakorn J. Development of Veress needle insertion robotic system and its experimental study for force acquisition in soft tissue. In: Proceeding of the IEEE International Conference on Robotics and Biomimetics (ROBIO), Shenzhen, 2013. 645–650

    Google Scholar 

  4. Elgezua I, Song S, Kobayashi Y, et al. Event classification in percutaneous treatments based on needle insertion force pattern analysis. In: Proceedings of the 13th International Conference on Control, Automation and Systems, Gwangju, 2013. 288–293

    Google Scholar 

  5. DiMaio S, Salcudean S. Interactive simulation of needle insertion models. IEEE Trans Biomed Eng, 2005, 52: 1167–1179

    Article  Google Scholar 

  6. Roesthuis R, van Veen Y, Jahya A, et al. Mechanics of needle-tissue interaction. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, San Francisco, 2011. 2557–2563

    Google Scholar 

  7. Kesner S, Howe R. Force control of flexible catheter robots for beating heart surgery. In: Proceedings of the IEEE International Conference on Robotics and Automation, Shanghai, 2011. 1589–1594

    Google Scholar 

  8. Polygerinos P, Puangmali P, Schaeffter T, et al. Novel miniature MRI-compatible fiber-optic force sensor for cardiac catheterization procedures. In: Proceedings of the IEEE International Conference on Robotics and Automation, Alaska, 2010. 2598–2603

    Google Scholar 

  9. Brett P, Harrison A, Thomas T. Schemes for the identification of tissue types and boundaries at the tool point for surgical needles. IEEE Trans Inf Technol Biomed, 2000, 4: 30–36

    Article  Google Scholar 

  10. Born M, Wolf E. Principles of Optics. Pergamon Press, 1964. Chapter

    Google Scholar 

  11. Zhu H. Development of a fiber optic force sensor and its application to identification of tissue types and boundaries. Dissertation for Master’s Degree. Beijing: Beijing Jiaotong Unversity, 2014

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to TangWen Yang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yang, T., Zhu, H., Han, J. et al. Identification of tissue types and boundaries with a fiber optic force sensor. Sci. China Inf. Sci. 57, 1–7 (2014). https://doi.org/10.1007/s11432-014-5218-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11432-014-5218-1

Keywords

Navigation